Good day po sir! Tienzo, Irish Jane BSIE - 1A Here's my three learning takeaways • I learned that the RANGE is the simplest measure of variability because it only requires finding the difference between the maximum and minimum values in a data set. • I learned that VARIANCE can be calculated for both sample data and population data, but the formula differs slightly depending on whether you’re dealing with a sample or the entire population. • I learned that STANDARD DEVIATION is more useful than range or variance when comparing two sets of data, because it gives a clearer idea of how consistent or variable the values are within each set.
Good day po sir! Tienzo, Irish Jane BSIE - 1A Here's my three learning takeaways • I learned that QUARTILES divide data into four parts, with each quartile representing a different portion of the data's distribution. • I learned that DECILES break data into ten equal parts, giving a more detailed view of data than quartiles. • I learned that PERCENTILES split data into 100 parts, helping to understand how a value compares to the entire dataset.
Good day Sir argie Sanchez BSIE 1-A Here are three key takeaways from **Measures of Variability**, focusing on **Range, Standard Deviation, and Variance**: 1. **Range Measures the Spread of Data**: - The **range** is the simplest measure of variability, calculated by subtracting the smallest value from the largest value in a dataset. It gives a quick sense of how spread out the values are, but it is sensitive to outliers and may not reflect the true dispersion in the dataset. 2. **Variance Quantifies Data Spread with Squared Differences**: - **Variance** measures how far each data point is from the mean, by calculating the average of the squared differences from the mean. A higher variance indicates that the data points are more spread out, while a lower variance suggests that the data points are closer to the mean. Variance is commonly used in statistical analysis, but its units are squared, which can make interpretation less intuitive. 3. **Standard Deviation Provides Intuitive Measure of Spread**: - **Standard deviation** is the square root of the variance, bringing it back to the original units of measurement. It is a more intuitive measure of variability, as it indicates how much the individual data points deviate, on average, from the mean. A larger standard deviation signifies greater spread or variability in the data, while a smaller standard deviation indicates less variation. These measures help assess the consistency, spread, or variability of data, which is crucial for understanding the reliability and variability of datasets.
Good Day Sir Argie Sanchez BSIE 1-A Here are three key takeaways from the concept of **Measures of Position**, focusing on **Quartiles, Deciles, and Percentiles**: 1. **Quartiles Divide Data into Four Equal Parts**: - The quartiles split a dataset into four equal parts. The first quartile (Q1) represents the 25th percentile, the second quartile (Q2, also the median) represents the 50th percentile, and the third quartile (Q3) represents the 75th percentile. Understanding quartiles helps to identify the spread and central tendency of the data. 2. **Deciles Split Data into Ten Equal Parts**: - Deciles break data into ten equal parts, providing a finer level of granularity than quartiles. The 1st decile (D1) corresponds to the 10th percentile, the 2nd decile (D2) to the 20th percentile, and so on, with the 9th decile (D9) representing the 90th percentile. This division helps to analyze the distribution in more detail, especially in large datasets. 3. **Percentiles Offer Precise Positioning**: - Percentiles divide data into 100 equal parts, giving a highly detailed view of the distribution. For instance, the 90th percentile indicates that 90% of the data points fall below this value. Percentiles are useful for comparing relative standings, such as test scores, where a high percentile indicates performance above most others. These measures help describe the relative position of values within a dataset, making it easier to understand its spread and make comparisons.
Good day, sir. Villanueva, Pauleen Joyce F. BSIE 1A Here are my 3 learning takeaways: In quartiles, the data is divided into four equal parts. Position refers to the relative placement of a data value in relation to the rest of the data. Relevance helps us assess our relative standing, especially when comparing performance or determining rankings.
Good Day, Sir! Kevin Clark Pangilinan BSIE-1A Three Learning Takeaways -Relevance refers to how meaningful and useful statistical measures, like quartiles and percentiles, are to understanding and interpreting specific data. -Position shows where a number is in a group of numbers, like its ranking. -Deciles divide data into 10 equal parts, showing where a value ranks from 1st to 10th part.
Good Day, Sir! Kevin Clark Pangilinan BSIE-1A Three Learning Takeaways -The range is the difference between the highest and lowest numbers in a group of numbers. To find the range, subtract the smallest number from the biggest number. -Measure of Central Tendency shows the middle or most common value in a group of numbers, like mean, median or mode. -Measure of Variability shows how spread out numbers are in a group, using range, variance and standard deviation.
Good day, Sir! Nicole Pajarillo BSIE 1A My three learning takeaways are: Range shows the gap between the smallest and largest values, acting as a measure of the data set's overall "length." Interquartile Range capptures the spread of the central portion of the data, focusing on the middle 50%. Standars Deviation reflects the average distance of data points from the mean, highlighting how dispersed the data is around the center.
Blessed day to you, Sir Mark Ren! Capagcuan, Bianca Alexis S. BSIE - 1A Here are my 3 takeaways: ☆Measures of variability are important since this provides context to data by describing the range of possible outcomes. ☆There are 3 Measures of Variability which all I have just learned how to solve. The Range, Variance, and Standard Deviation. ☆In order for the variability in data to be represented, you must first understand the degree to which data values are distributed that can be solved by using basic or simple measures.
Good day sir! Villanueva, Pauleen Joyce F. BSIE 1A My three learning takeaways 1. Range, Standard Deviation and Variance are tools to measure the variability. The range looks at the difference between the highest and lowest values, while variance and standard deviation show how much each value differs from the average. 2. Mean, median, and mode describe the center of the data. The mean is the average, the median is the middle value, and the mode is the most common value in the dataset. 3. Measures of central tendency and variability work together to give a complete picture of the data. Central tendency shows where the data is centered, and variability shows how much the data spreads around that center.
Hipol, Jelian Angel S. BSIE-1A My three learnings takeaways: One of the Statistical Tools in Evaluation is Measures of Variability it is describes the set of scores in terms of their spread, or heterogeneity. So there are three measures to measures of Variability this are Range, Standard Deviation and Variance. •Range - easiest measures of variability to calculate, used when the measure of central tendency is the mode. •Standard deviation measures variability in normally distributed interval or ratio data. It shows how much scores deviate from the mean-the greater the differences, the higher the standard deviation. •Variance is used in advanced statistical methods like regression and anova. it is the square of the standard deviation (s²).
Blessed day to you, Sir Mark Ren! Capagcuan, Bianca Alexis S. BSIE- 1A Here are my 3 takeaways: ☆ Measures of positions are important in our daily lives because we are able to use Statistics effectively for research purposes and more. ☆Learning and understanding Measures of position leads to better outcomes and decision makings. ☆Measures are able to determine whether a value of something is an average, low or high. This is used for Quantitative datas that have some numerical scale
Good day sir Ian Kervie Francisco Valiente BSIE-1B My Three learning takeaways Position is used to describe the position of a data value in relation to the rest of the data.There are three types of position this are Quartile, Percentile and Deciles Deciles break data into ten equal sections Quartiles Values of the variables are divided in to quarters- 4 equal parts.
Good day Sir! Nicole Pajarillo BSIE 1A My three learning takeaways: Q1 (Lower Quartile): Splits the lower half of the data set into two equal parts. Median: Divides the entire data set into two equal halves. Q3 (Upper Quartile): Splits the upper half of the data set into two equal parts, with at most 25% of the data being greater than Q3.
Good day sir Ian Kervie Francisco Valiente BSIE-1B My Three learning takeaways Measure of Center Tendency looks for the average and most common measures called mean. Range; showing the difference between the smallest and largest values. It's like measuring the length of our data set Variance measures how far each number in a dataset is from the mean (average) and thus from every other number. It is the average of the squared differences from the mean.
Good day, Sir! Hipol, Jelian Angel S. BSIE-1A My three learnings takeaways. Relevance is to be able to evaluate our relative position when interested in comparing performance and knowing a ranking. and decides what is the relevance. Position is used to describe the position of a data value in relation to the rest of the data.There are three types of position this are Quartile, Percentile and Deciles •Quartiles-Values of the variables are divided into quarters - 4 equal parts. They are called Q1 Q2 Q3 •Percentiles- Values of the variable that divide a ranked set into 100 subsets. For example, P30 would be at 30% •Deciles- it is divides data into 10 equal parts, with each part representing 10% of the dataset.
Good day, Sir! Cristobal, Danna S. BSIE - A My three learning take ways 1. The range is the basic measure of variability indicating the difference between the highest and lowest values in a dataset. 2. Measures of central tendency are statistical tools that identify the center or typical value in a dataset, summarizing it with a single representative value. 3. Measures of variability are statistical tools that describe the spread of data in a dataset, showing how much values differ from each other and from the central tendency.
Joshua Paul D.Cuares BSIE- 1-A Three learning takeaways 1. Standard Deviation -indicates the amount that all scores differ or deviate from the mean. 2. Range Easiest measure of variability to calculate 3. Measure of Variability It describes the set of scores in terms of their spread, or heterogeneity.
GOOD DAY SIR! Macabanti, Mark Romer M. BSIE 1-A MY THREE LEARNING TAKEAWAYS Measures of position help us understand the relative position of a value within a data set. Quartiles, deciles, and percentiles divide the data into equal parts to identify ranks or percentages. These measures are useful in analyzing grades, income distribution, and performance rankings in real life.
Joshua Paul D.Cuares BSIE- 1-A Three learning takeaways 1. Position It is used to describe the position of data value in relation to the rest of the data. 2.Relevance To evaluate our relative position when we are comparing performance and knowing a ranking. 3.Quartiles Values of the variables are divided in to quarters- 4 equal parts.
Good day sir! Hementera, Princess F. BSIE 1A -Upon watching this video, I learned that almost everything in our lives, and everyday.. we are using statistics. This video helps me understand how to measure different variabilities. -I learned that the measures of variability is how the set of data is spread out. -Measure of Center Tendency looks for the average and most common measures called mean.
GOOD DAY SIR! Macabanti, Mark Romer M. BSIE 1-A MY THREE LEARNING TAKEAWAYS Measures of variability show how spread out or different the data values are from each other. Standard deviation tells us the average distance of each value from the mean, helping us see if the data is close together or spread out. Variance is the squared value of the standard deviation and is used to compare or analyze data in more detail.
Good day, Sir! Cristobal, Danna S. BSIE - 1A Relevance: it helps us evaluate our relative position when we want to compare performance or knowing a rankings. Quartiles: quartiles divide ordered data into four equal sections. Position: it explains a data values position compared to other data.
Good Day sir. Raylee C. De Guzman BSIE-1A upon this topic I've learned that the range is the simplest measure of variability, showing the difference between the highest and lowest values in a dataset. Measures of central tendency, such as the mean, median, and mode, are statistical tools used to determine the center or typical value in a dataset, summarizing the data by focusing on a single representative value. Complementing these, measures of variability describe the spread or dispersion of data within a dataset, indicating how much the data values differ from each other and from the central tendency. Together, these measures provide a comprehensive understanding of a dataset's characteristics.
Good day Sir. Raylee C. De Guzman BSIE-1A In this topic, I learned that there are 3 types to describe the position of a data value in relation to the rest of the data, which are Quartile, percentile, and Decile. Percentile indicates the position of a data point relative to the rest of the data, dividing it into 100 equal parts for example: the 90th percentile is the value below which 90% of the data falls. Decile divides data into 10 equal parts, with each decile representing 10% of the data distribution for example: the 3rd decile marks the top 30%. Quartile splits data into four equal parts, highlighting key points like the median (Q2 and interquartile range (Q1 to Q3) to measure data spread.
Good day Sir! De Guzman Myles E. BSIE 1-B Overall, studying the measures of position plays an integral part in the most aspect of human life. It give us a way to see where a certain data point or value falls in a sample or distribution. A measure can tell us whether a value is about the average, or whether it's unusually high or low.
Good day po, Sir!! Emanil, Aldwin C. BSIE-1A -Percentiles divide a dataset into 100 equal parts, indicating the percentage of data points below a certain value. - Quartiles divide a dataset into four equal parts, highlighting the spread of data within specific portions of the distribution. -Z-scores standardize data points by comparing them to the mean and standard deviation, allowing for comparisons across different datasets.
Good day, Sir! Maguate, Jemiely B. BSIE 1-A My three learning takeaways: * Q1- Lower Quartile divides the lower half of a data set in half. * Q2- Median divides the data set in half. * Q3- Upper Quartile divides the upper half of the a data set in half. At most, 25% of data is larger than Q3.
good day sir🫶 FRANK MOISES LINDE BSIE 1A my 3 learning takeaways Measures of Variability Range, standard deviation, and variance quantify data spread. Real-World Usage These measures aid decision-making in finance, healthcare, social sciences and quality control. Interpretation Understanding variability helps identify patterns, outliers and correlations, informing data-driven insights.
Good day, Sir! Maguate, Jemiely B. BSIE 1-A My three learning takeaways: * Measures of variability describe how far apart data points lie from each other and from the center of a distribution. * A range is the complete group that is included between two points on a scale of measurement or quality. * Standard deviation is a statistical measurement that looks at how far individual points in a dataset are dispersed from the mean of that set.
good day sir🫶 FRANK MOISES LINDE BSIE 1A my 3 learning takeaways - Quartiles, deciles, and percentiles divide data into equal parts. -Used in statistics, data analysis, and decision-making. - Enable effective data visualization, comparison, and insight communication.
Good day sir!! Rivera Micah Claire From BSIE 1A My three learning takeaways Range; showing the difference between the smallest and largest values. It's like measuring the length of our data set Interquartile range: measure the middle of our data The standard deviation measures how much, on average, our data points deviate from the mean. It's like a measure of how spread out our data is around the center.
Jasmine Agulto BSIE 1-A Range: the difference between the highest and lowest numbers. Interquartile Range: The center part of a distribution's range is known. The average difference from the mean is called the standard deviation.
Good day, sir!! Medestomas, Joseph R. BSIE - 1A My 3 Learning takeaways: 1. The range is the simplest measure of variability. It shows the difference between the highest and lowest values in a dataset. 2. Measures of central tendency are statistical tools for determining the center or typical value in a dataset. They summarize the data by focusing on a single representative value. 3. Measures of variability are statistical tools used to describe the spread or dispersion of data within a dataset. They indicate how much the data values differ from each other and from the central tendency.
Good day po, Sir! Emanil, Aldwin C. BSIE-1A MY THREE LEARNING TAKEAWAYS: -Variability describes how spread out data is. It tells us how much individual data points differ from the average or central tendency. High variability means data is widely scattered, while low variability indicates data points are clustered close together. -Range is the difference between the highest and lowest values. Simple but sensitive to outliers. -Compare groups: Variability helps determine if differences between groups are significant or due to random chance.
Agulto Jasmine M. Bsie 1- A My Three Learning takeaways are: 1.Relevance: If we are aware of rankings, it aids in assessing our relative position when comparing performance. 2.Quartiles divide ordered data into four equal parts, the first quartile (Q1) is the 25th percentile, the second quartile (Q2 or median) is the 50th percentile, and the third quartile (Q3) is the 75th percentile. Deciles divide ordered data into ten equal parts, with each decile representing a 10% increment in the data distribution. 3. Position: Describes how a data value is positioned in relation to the other data.
ALDRICH A. PANGILINAN BSIE 1 A My three learning takeways Measures of central tendency look at the average which is mean, median and mode while Measures of Variability looked at how close and similar a given set of data Range: the distinction between the maximum and minimum values. The standard deviation is the square root of the variance. It gives a measure of the average distance between each data point and the mean, in the original units of the data (unlike variance, which is in squared units).
Good day sir!! Rivera Micah Claire From BSIE 1A My three learning takeaways Position: Measures of position show us where a data value fits within a dataset, comparing it to the rest. Quartiles: the variable is equal to four Q1 being the highest and Q2 and Q3 are the lowest Relevance: Rankings help us easily see how we compare to others, making it simple to understand our performance and set goals for improvement.
Good day, sir!! Medestomas, Joseph R. BSIE - 1A My 3 Learning takeaways: 1. In Relevance it help us to be able to evaluate our relative positions when interested in comparing performance and knowing a ranking. 2. In Position it is used to describe the position of a data value in relation to the rest of the data and there is three types of position quartiles, percentiles and deciles. 3.Measure of position using several methods to separate data into equal groups. These values indicate the value's location within the data set in relation to other values. To calculate the measure of position, the data must be sorted in ascending order.
Good Day Sir! Reyes, Nicole B. BSIE 1A The range is the simplest measure of variability. It shows the difference between the highest and lowest values in a dataset. Variance measures how far each number in a dataset is from the mean (average) and thus from every other number. It is the average of the squared differences from the mean. The standard deviation is the square root of the variance. It gives a measure of the average distance between each data point and the mean, in the original units of the data (unlike variance, which is in squared units).
ALDRICH A PANGILINAN BSIE 1 A Deciles are helpful when comparing groups, especially in large datasets like income distribution. Position: Used to describe a data value's position relative to the remainder of the data. Percentiles and quartiles are widely used, such as in education to interpret test scores, or in business to compare performance metrics.
Good day sir! Reyes Nicole BSIE-1A The 4 equal parts are Q1 first quartile Q2 Second quartile Q3 third quartile Q4 fourth quartile but the Q4 will not solve because its set of order ascending order. First Quartile (Q1): Also called the lower quartile, it is the median of the lower half of the dataset (25th percentile). It marks the point where 25% of the data lies below it. Second Quartile (Q2): This is the median of the entire dataset (50th percentile). It divides the data into two equal halves. Third Quartile (Q3): Also called the upper quartile, it is the median of the upper half of the dataset (75th percentile). It marks the point where 75% of the data lies below it.
Good Day po Sir! MG S. Miranda BSIE-1B My 3 Takeaways for this lesson ●Measures of variability like range, standard deviation, and variance show how spread out the data is. ●These two tell us how far data points are from the average, helping us see if data is consistent or scattered. ●The range is the simplest one, it’s the difference between the highest and lowest values in the data.
Good day po sir Mejia,Kristalyn M. BSIE 1-A My three learnings takeaways Measures of central tendency are statistical tools for determining the center or typical value in a dataset. They summarize the data by focusing on a single representative value. Measures of variability are statistical tools used to describe the spread or dispersion of data within a dataset. They indicate how much the data values differ from each other and from the central tendency. Range: The difference between the maximum and minimum values in the dataset.
Romulo, Mia Jerlyn R. BSIE 1A My Three Learning Takeaways: 1. Measures of variability it is used to describes the set of scores in terms of their apread, or heterogeneity. 2. Range is the easiest measure of variability to calculate. 3. Standard Deviation it is used to measure variability with the mean.
Good day po Sir! MG S. Miranda BSIE-1B My 3 takeaways for this lesson ●Quartiles, deciles, and percentiles divide data into smaller parts and quartiles into 4, deciles into 10, and percentiles into 100. ●These measures can help you decide things like which school to choose, which job offer is better, or even how you rank in a competition. ●They are useful in real life for analyzing test scores, salaries, or survey results to better understand data and other stuff.
Good Day po! Sia, Anna Rose Trisha S. BSIE 1A Range is the simplest measure, but it can be affected by extreme values (outliers). Variance measures the spread of data but is in squared units, making it harder to interpret directly. Standard Deviation is the most commonly used measure of spread, as it is in the same units as the data and gives an intuitive understanding of how spread out the data is.
Good day sir! Hementera, Princess F. BSIE 1A -There are also three types the measure of position which are the Percentiles, Decides and the Quartiles. -Deciles break data into ten equal sections. -I learned that the measures of position identities the location of the single value in the data.
Good Day po Sir! Sia, Anna Rose Trisha S. BSIE 1A Quartiles are commonly used in box plots to visualize the spread and central tendency of the data. Deciles are helpful when comparing groups, especially in large datasets like income distribution. Percentiles are frequently used in standardized testing, health metrics, and performance comparisons (e.g., a student in the 90th percentile has scored better than 90% of their peers).
Good day po sir! Tienzo, Irish Jane BSIE - 1A Here's my three learning takeaways • I learned that the RANGE is the simplest measure of variability because it only requires finding the difference between the maximum and minimum values in a data set. • I learned that VARIANCE can be calculated for both sample data and population data, but the formula differs slightly depending on whether you’re dealing with a sample or the entire population. • I learned that STANDARD DEVIATION is more useful than range or variance when comparing two sets of data, because it gives a clearer idea of how consistent or variable the values are within each set.
Good day po sir! Tienzo, Irish Jane BSIE - 1A Here's my three learning takeaways • I learned that QUARTILES divide data into four parts, with each quartile representing a different portion of the data's distribution. • I learned that DECILES break data into ten equal parts, giving a more detailed view of data than quartiles. • I learned that PERCENTILES split data into 100 parts, helping to understand how a value compares to the entire dataset.
Good day Sir argie Sanchez BSIE 1-A Here are three key takeaways from **Measures of Variability**, focusing on **Range, Standard Deviation, and Variance**: 1. **Range Measures the Spread of Data**: - The **range** is the simplest measure of variability, calculated by subtracting the smallest value from the largest value in a dataset. It gives a quick sense of how spread out the values are, but it is sensitive to outliers and may not reflect the true dispersion in the dataset. 2. **Variance Quantifies Data Spread with Squared Differences**: - **Variance** measures how far each data point is from the mean, by calculating the average of the squared differences from the mean. A higher variance indicates that the data points are more spread out, while a lower variance suggests that the data points are closer to the mean. Variance is commonly used in statistical analysis, but its units are squared, which can make interpretation less intuitive. 3. **Standard Deviation Provides Intuitive Measure of Spread**: - **Standard deviation** is the square root of the variance, bringing it back to the original units of measurement. It is a more intuitive measure of variability, as it indicates how much the individual data points deviate, on average, from the mean. A larger standard deviation signifies greater spread or variability in the data, while a smaller standard deviation indicates less variation. These measures help assess the consistency, spread, or variability of data, which is crucial for understanding the reliability and variability of datasets.
Good Day Sir Argie Sanchez BSIE 1-A Here are three key takeaways from the concept of **Measures of Position**, focusing on **Quartiles, Deciles, and Percentiles**: 1. **Quartiles Divide Data into Four Equal Parts**: - The quartiles split a dataset into four equal parts. The first quartile (Q1) represents the 25th percentile, the second quartile (Q2, also the median) represents the 50th percentile, and the third quartile (Q3) represents the 75th percentile. Understanding quartiles helps to identify the spread and central tendency of the data. 2. **Deciles Split Data into Ten Equal Parts**: - Deciles break data into ten equal parts, providing a finer level of granularity than quartiles. The 1st decile (D1) corresponds to the 10th percentile, the 2nd decile (D2) to the 20th percentile, and so on, with the 9th decile (D9) representing the 90th percentile. This division helps to analyze the distribution in more detail, especially in large datasets. 3. **Percentiles Offer Precise Positioning**: - Percentiles divide data into 100 equal parts, giving a highly detailed view of the distribution. For instance, the 90th percentile indicates that 90% of the data points fall below this value. Percentiles are useful for comparing relative standings, such as test scores, where a high percentile indicates performance above most others. These measures help describe the relative position of values within a dataset, making it easier to understand its spread and make comparisons.
Good day, sir. Villanueva, Pauleen Joyce F. BSIE 1A Here are my 3 learning takeaways: In quartiles, the data is divided into four equal parts. Position refers to the relative placement of a data value in relation to the rest of the data. Relevance helps us assess our relative standing, especially when comparing performance or determining rankings.
Good Day, Sir! Kevin Clark Pangilinan BSIE-1A Three Learning Takeaways -Relevance refers to how meaningful and useful statistical measures, like quartiles and percentiles, are to understanding and interpreting specific data. -Position shows where a number is in a group of numbers, like its ranking. -Deciles divide data into 10 equal parts, showing where a value ranks from 1st to 10th part.
Good Day, Sir! Kevin Clark Pangilinan BSIE-1A Three Learning Takeaways -The range is the difference between the highest and lowest numbers in a group of numbers. To find the range, subtract the smallest number from the biggest number. -Measure of Central Tendency shows the middle or most common value in a group of numbers, like mean, median or mode. -Measure of Variability shows how spread out numbers are in a group, using range, variance and standard deviation.
Good day, Sir! Nicole Pajarillo BSIE 1A My three learning takeaways are: Range shows the gap between the smallest and largest values, acting as a measure of the data set's overall "length." Interquartile Range capptures the spread of the central portion of the data, focusing on the middle 50%. Standars Deviation reflects the average distance of data points from the mean, highlighting how dispersed the data is around the center.
Blessed day to you, Sir Mark Ren! Capagcuan, Bianca Alexis S. BSIE - 1A Here are my 3 takeaways: ☆Measures of variability are important since this provides context to data by describing the range of possible outcomes. ☆There are 3 Measures of Variability which all I have just learned how to solve. The Range, Variance, and Standard Deviation. ☆In order for the variability in data to be represented, you must first understand the degree to which data values are distributed that can be solved by using basic or simple measures.
Good day sir! Villanueva, Pauleen Joyce F. BSIE 1A My three learning takeaways 1. Range, Standard Deviation and Variance are tools to measure the variability. The range looks at the difference between the highest and lowest values, while variance and standard deviation show how much each value differs from the average. 2. Mean, median, and mode describe the center of the data. The mean is the average, the median is the middle value, and the mode is the most common value in the dataset. 3. Measures of central tendency and variability work together to give a complete picture of the data. Central tendency shows where the data is centered, and variability shows how much the data spreads around that center.
Hipol, Jelian Angel S. BSIE-1A My three learnings takeaways: One of the Statistical Tools in Evaluation is Measures of Variability it is describes the set of scores in terms of their spread, or heterogeneity. So there are three measures to measures of Variability this are Range, Standard Deviation and Variance. •Range - easiest measures of variability to calculate, used when the measure of central tendency is the mode. •Standard deviation measures variability in normally distributed interval or ratio data. It shows how much scores deviate from the mean-the greater the differences, the higher the standard deviation. •Variance is used in advanced statistical methods like regression and anova. it is the square of the standard deviation (s²).
Blessed day to you, Sir Mark Ren! Capagcuan, Bianca Alexis S. BSIE- 1A Here are my 3 takeaways: ☆ Measures of positions are important in our daily lives because we are able to use Statistics effectively for research purposes and more. ☆Learning and understanding Measures of position leads to better outcomes and decision makings. ☆Measures are able to determine whether a value of something is an average, low or high. This is used for Quantitative datas that have some numerical scale
Good day sir Ian Kervie Francisco Valiente BSIE-1B My Three learning takeaways Position is used to describe the position of a data value in relation to the rest of the data.There are three types of position this are Quartile, Percentile and Deciles Deciles break data into ten equal sections Quartiles Values of the variables are divided in to quarters- 4 equal parts.
Good day Sir! Nicole Pajarillo BSIE 1A My three learning takeaways: Q1 (Lower Quartile): Splits the lower half of the data set into two equal parts. Median: Divides the entire data set into two equal halves. Q3 (Upper Quartile): Splits the upper half of the data set into two equal parts, with at most 25% of the data being greater than Q3.
Good day sir Ian Kervie Francisco Valiente BSIE-1B My Three learning takeaways Measure of Center Tendency looks for the average and most common measures called mean. Range; showing the difference between the smallest and largest values. It's like measuring the length of our data set Variance measures how far each number in a dataset is from the mean (average) and thus from every other number. It is the average of the squared differences from the mean.
Good day, Sir! Hipol, Jelian Angel S. BSIE-1A My three learnings takeaways. Relevance is to be able to evaluate our relative position when interested in comparing performance and knowing a ranking. and decides what is the relevance. Position is used to describe the position of a data value in relation to the rest of the data.There are three types of position this are Quartile, Percentile and Deciles •Quartiles-Values of the variables are divided into quarters - 4 equal parts. They are called Q1 Q2 Q3 •Percentiles- Values of the variable that divide a ranked set into 100 subsets. For example, P30 would be at 30% •Deciles- it is divides data into 10 equal parts, with each part representing 10% of the dataset.
Good day, Sir! Cristobal, Danna S. BSIE - A My three learning take ways 1. The range is the basic measure of variability indicating the difference between the highest and lowest values in a dataset. 2. Measures of central tendency are statistical tools that identify the center or typical value in a dataset, summarizing it with a single representative value. 3. Measures of variability are statistical tools that describe the spread of data in a dataset, showing how much values differ from each other and from the central tendency.
Joshua Paul D.Cuares BSIE- 1-A Three learning takeaways 1. Standard Deviation -indicates the amount that all scores differ or deviate from the mean. 2. Range Easiest measure of variability to calculate 3. Measure of Variability It describes the set of scores in terms of their spread, or heterogeneity.
GOOD DAY SIR! Macabanti, Mark Romer M. BSIE 1-A MY THREE LEARNING TAKEAWAYS Measures of position help us understand the relative position of a value within a data set. Quartiles, deciles, and percentiles divide the data into equal parts to identify ranks or percentages. These measures are useful in analyzing grades, income distribution, and performance rankings in real life.
Joshua Paul D.Cuares BSIE- 1-A Three learning takeaways 1. Position It is used to describe the position of data value in relation to the rest of the data. 2.Relevance To evaluate our relative position when we are comparing performance and knowing a ranking. 3.Quartiles Values of the variables are divided in to quarters- 4 equal parts.
Good day sir! Hementera, Princess F. BSIE 1A -Upon watching this video, I learned that almost everything in our lives, and everyday.. we are using statistics. This video helps me understand how to measure different variabilities. -I learned that the measures of variability is how the set of data is spread out. -Measure of Center Tendency looks for the average and most common measures called mean.
Jhon Steven Alcantara BSIE-1B
GOOD DAY SIR! Macabanti, Mark Romer M. BSIE 1-A MY THREE LEARNING TAKEAWAYS Measures of variability show how spread out or different the data values are from each other. Standard deviation tells us the average distance of each value from the mean, helping us see if the data is close together or spread out. Variance is the squared value of the standard deviation and is used to compare or analyze data in more detail.
Good day, Sir! Cristobal, Danna S. BSIE - 1A Relevance: it helps us evaluate our relative position when we want to compare performance or knowing a rankings. Quartiles: quartiles divide ordered data into four equal sections. Position: it explains a data values position compared to other data.
Good Day sir. Raylee C. De Guzman BSIE-1A upon this topic I've learned that the range is the simplest measure of variability, showing the difference between the highest and lowest values in a dataset. Measures of central tendency, such as the mean, median, and mode, are statistical tools used to determine the center or typical value in a dataset, summarizing the data by focusing on a single representative value. Complementing these, measures of variability describe the spread or dispersion of data within a dataset, indicating how much the data values differ from each other and from the central tendency. Together, these measures provide a comprehensive understanding of a dataset's characteristics.
Good day Sir. Raylee C. De Guzman BSIE-1A In this topic, I learned that there are 3 types to describe the position of a data value in relation to the rest of the data, which are Quartile, percentile, and Decile. Percentile indicates the position of a data point relative to the rest of the data, dividing it into 100 equal parts for example: the 90th percentile is the value below which 90% of the data falls. Decile divides data into 10 equal parts, with each decile representing 10% of the data distribution for example: the 3rd decile marks the top 30%. Quartile splits data into four equal parts, highlighting key points like the median (Q2 and interquartile range (Q1 to Q3) to measure data spread.
Good day Sir! De Guzman Myles E. BSIE 1-B Overall, studying the measures of position plays an integral part in the most aspect of human life. It give us a way to see where a certain data point or value falls in a sample or distribution. A measure can tell us whether a value is about the average, or whether it's unusually high or low.
Good day po, Sir!! Emanil, Aldwin C. BSIE-1A -Percentiles divide a dataset into 100 equal parts, indicating the percentage of data points below a certain value. - Quartiles divide a dataset into four equal parts, highlighting the spread of data within specific portions of the distribution. -Z-scores standardize data points by comparing them to the mean and standard deviation, allowing for comparisons across different datasets.
Good day, Sir! Maguate, Jemiely B. BSIE 1-A My three learning takeaways: * Q1- Lower Quartile divides the lower half of a data set in half. * Q2- Median divides the data set in half. * Q3- Upper Quartile divides the upper half of the a data set in half. At most, 25% of data is larger than Q3.
good day sir🫶 FRANK MOISES LINDE BSIE 1A my 3 learning takeaways Measures of Variability Range, standard deviation, and variance quantify data spread. Real-World Usage These measures aid decision-making in finance, healthcare, social sciences and quality control. Interpretation Understanding variability helps identify patterns, outliers and correlations, informing data-driven insights.
Good day, Sir! Maguate, Jemiely B. BSIE 1-A My three learning takeaways: * Measures of variability describe how far apart data points lie from each other and from the center of a distribution. * A range is the complete group that is included between two points on a scale of measurement or quality. * Standard deviation is a statistical measurement that looks at how far individual points in a dataset are dispersed from the mean of that set.
good day sir🫶 FRANK MOISES LINDE BSIE 1A my 3 learning takeaways - Quartiles, deciles, and percentiles divide data into equal parts. -Used in statistics, data analysis, and decision-making. - Enable effective data visualization, comparison, and insight communication.
Good day sir!! Rivera Micah Claire From BSIE 1A My three learning takeaways Range; showing the difference between the smallest and largest values. It's like measuring the length of our data set Interquartile range: measure the middle of our data The standard deviation measures how much, on average, our data points deviate from the mean. It's like a measure of how spread out our data is around the center.
Jasmine Agulto BSIE 1-A Range: the difference between the highest and lowest numbers. Interquartile Range: The center part of a distribution's range is known. The average difference from the mean is called the standard deviation.
Good day, sir!! Medestomas, Joseph R. BSIE - 1A My 3 Learning takeaways: 1. The range is the simplest measure of variability. It shows the difference between the highest and lowest values in a dataset. 2. Measures of central tendency are statistical tools for determining the center or typical value in a dataset. They summarize the data by focusing on a single representative value. 3. Measures of variability are statistical tools used to describe the spread or dispersion of data within a dataset. They indicate how much the data values differ from each other and from the central tendency.
Good day po, Sir! Emanil, Aldwin C. BSIE-1A MY THREE LEARNING TAKEAWAYS: -Variability describes how spread out data is. It tells us how much individual data points differ from the average or central tendency. High variability means data is widely scattered, while low variability indicates data points are clustered close together. -Range is the difference between the highest and lowest values. Simple but sensitive to outliers. -Compare groups: Variability helps determine if differences between groups are significant or due to random chance.
Agulto Jasmine M. Bsie 1- A My Three Learning takeaways are: 1.Relevance: If we are aware of rankings, it aids in assessing our relative position when comparing performance. 2.Quartiles divide ordered data into four equal parts, the first quartile (Q1) is the 25th percentile, the second quartile (Q2 or median) is the 50th percentile, and the third quartile (Q3) is the 75th percentile. Deciles divide ordered data into ten equal parts, with each decile representing a 10% increment in the data distribution. 3. Position: Describes how a data value is positioned in relation to the other data.
ALDRICH A. PANGILINAN BSIE 1 A My three learning takeways Measures of central tendency look at the average which is mean, median and mode while Measures of Variability looked at how close and similar a given set of data Range: the distinction between the maximum and minimum values. The standard deviation is the square root of the variance. It gives a measure of the average distance between each data point and the mean, in the original units of the data (unlike variance, which is in squared units).
Good day sir!! Rivera Micah Claire From BSIE 1A My three learning takeaways Position: Measures of position show us where a data value fits within a dataset, comparing it to the rest. Quartiles: the variable is equal to four Q1 being the highest and Q2 and Q3 are the lowest Relevance: Rankings help us easily see how we compare to others, making it simple to understand our performance and set goals for improvement.
Good day, sir!! Medestomas, Joseph R. BSIE - 1A My 3 Learning takeaways: 1. In Relevance it help us to be able to evaluate our relative positions when interested in comparing performance and knowing a ranking. 2. In Position it is used to describe the position of a data value in relation to the rest of the data and there is three types of position quartiles, percentiles and deciles. 3.Measure of position using several methods to separate data into equal groups. These values indicate the value's location within the data set in relation to other values. To calculate the measure of position, the data must be sorted in ascending order.
Good Day Sir! Reyes, Nicole B. BSIE 1A The range is the simplest measure of variability. It shows the difference between the highest and lowest values in a dataset. Variance measures how far each number in a dataset is from the mean (average) and thus from every other number. It is the average of the squared differences from the mean. The standard deviation is the square root of the variance. It gives a measure of the average distance between each data point and the mean, in the original units of the data (unlike variance, which is in squared units).
ALDRICH A PANGILINAN BSIE 1 A Deciles are helpful when comparing groups, especially in large datasets like income distribution. Position: Used to describe a data value's position relative to the remainder of the data. Percentiles and quartiles are widely used, such as in education to interpret test scores, or in business to compare performance metrics.
Good day sir! Reyes Nicole BSIE-1A The 4 equal parts are Q1 first quartile Q2 Second quartile Q3 third quartile Q4 fourth quartile but the Q4 will not solve because its set of order ascending order. First Quartile (Q1): Also called the lower quartile, it is the median of the lower half of the dataset (25th percentile). It marks the point where 25% of the data lies below it. Second Quartile (Q2): This is the median of the entire dataset (50th percentile). It divides the data into two equal halves. Third Quartile (Q3): Also called the upper quartile, it is the median of the upper half of the dataset (75th percentile). It marks the point where 75% of the data lies below it.
Good Day po Sir! MG S. Miranda BSIE-1B My 3 Takeaways for this lesson ●Measures of variability like range, standard deviation, and variance show how spread out the data is. ●These two tell us how far data points are from the average, helping us see if data is consistent or scattered. ●The range is the simplest one, it’s the difference between the highest and lowest values in the data.
Good day po sir Mejia,Kristalyn M. BSIE 1-A My three learnings takeaways Measures of central tendency are statistical tools for determining the center or typical value in a dataset. They summarize the data by focusing on a single representative value. Measures of variability are statistical tools used to describe the spread or dispersion of data within a dataset. They indicate how much the data values differ from each other and from the central tendency. Range: The difference between the maximum and minimum values in the dataset.
Romulo, Mia Jerlyn R. BSIE 1A My Three Learning Takeaways: 1. Measures of variability it is used to describes the set of scores in terms of their apread, or heterogeneity. 2. Range is the easiest measure of variability to calculate. 3. Standard Deviation it is used to measure variability with the mean.
Good day po Sir! MG S. Miranda BSIE-1B My 3 takeaways for this lesson ●Quartiles, deciles, and percentiles divide data into smaller parts and quartiles into 4, deciles into 10, and percentiles into 100. ●These measures can help you decide things like which school to choose, which job offer is better, or even how you rank in a competition. ●They are useful in real life for analyzing test scores, salaries, or survey results to better understand data and other stuff.
Good Day po! Sia, Anna Rose Trisha S. BSIE 1A Range is the simplest measure, but it can be affected by extreme values (outliers). Variance measures the spread of data but is in squared units, making it harder to interpret directly. Standard Deviation is the most commonly used measure of spread, as it is in the same units as the data and gives an intuitive understanding of how spread out the data is.
Good day sir! Hementera, Princess F. BSIE 1A -There are also three types the measure of position which are the Percentiles, Decides and the Quartiles. -Deciles break data into ten equal sections. -I learned that the measures of position identities the location of the single value in the data.
Good Day po Sir! Sia, Anna Rose Trisha S. BSIE 1A Quartiles are commonly used in box plots to visualize the spread and central tendency of the data. Deciles are helpful when comparing groups, especially in large datasets like income distribution. Percentiles are frequently used in standardized testing, health metrics, and performance comparisons (e.g., a student in the 90th percentile has scored better than 90% of their peers).