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Arman Hossain Chowdhury
Добавлен 27 сен 2021
The purpose of this channel is to share educative and R programming videos.
LASSO Regression in R
Statistical analysis frequently employs regression models. One such application is simulating the expected risk of a foreseeable event. Unfortunately, using standard regression techniques to create a model from a set of candidate variables often results in overfitting (i.e., adding too many variables) and overestimation (i.e., optimism bias) of the model's ability to explain the observed variability using the included variables. A kind of linear regression known as Lasso regression, or least absolute shrinkage and selection operator, incorporates a penalty proportional to the true amount of the magnitude of the coefficients. This penalty makes certain coefficients absolutely zero, allowin...
Просмотров: 30
Видео
Polynomial Regression Model in R
Просмотров 773 месяца назад
In polynomial regression, an nth-degree polynomial is used to describe the association between the independent variable (predictor) and the dependent variable (response). Put another way, polynomial regression fits a curve to the data rather than a straight line, as in basic linear regression, or a plane, as in multiple linear regression.
Skewness and Kurtosis in R
Просмотров 1124 месяца назад
A distribution's symmetry is measured by its skewness. If there is a greater concentration of data on one side of the mean than the other, this is indicated. For a symmetric distribution, the mode, median, and mean are all equal, and the skewness value is 0. Data is skewed towards higher values when there is positive skewness (greater than zero), which is indicative of a longer tail on the righ...
ANOVA in SPSS | Part 2: Two-way anova
Просмотров 676 месяцев назад
Two-way analysis of variance, or ANOVA, is a statistical technique that examines how two categorical independent variables affect a continuous dependent variable. It builds on the ideas of one-way ANOVA, which examines the effects of a single independent variable. Two independent variables, also referred to as factors, are present in a two-way ANOVA. There might be two or more tiers or categori...
ANOVA in SPSS | Part 1: One-way anova
Просмотров 1296 месяцев назад
A statistical technique called one-way analysis of variance (ANOVA) is used to compare the means of three or more groups and see if there are any statistically significant differences between them. It is an expansion of the t-test, which is employed to compare two groups' means. Assumptions: 1.Observational independence 2.Normality 3.Homogeneity of variances
Chi square Test in SPSS
Просмотров 1686 месяцев назад
The Chi-square test examines variations between categorical variables in a random sample to ascertain if the predicted and actual findings are well-fitted. The core idea behind the test is to compare the observed values in your data to the values that would be expected if the null hypothesis were correct.
Factor Analysis Real Life Example | A presentation on Factor Analysis| Dept. of Statistics, BRUR
Просмотров 135Год назад
A statistical technique known as factor analysis is used to explain variation among associated, observable variables in terms of a conceivably smaller set of unseen variables known as factors. For instance, it's feasible that changes in six variables that have been detected mostly reflect changes in two variables that haven't been measured.
Multicollinearity Detection and its Interpretation in R
Просмотров 384Год назад
Multicollinearity is the existence of strong correlations between two or more predictor variables in a multiple regression model. When a researcher or analyst tries to figure out how each independent variable might be utilized to predict or comprehend the dependent variable in a statistical model, multicollinearity can result in skewed or misleading results. Different methods of detecting multi...
Logistic Regression Analysis in R
Просмотров 187Год назад
Logistic Regression is the most widely used and a popular method for modelling the binary response variable with one or more independent variable. It is frequently used in the fields of machine learning and data analysis to forecast the likelihood of an event occurring based on a collection of input factors.
Outlier Detection Techniques in R
Просмотров 1,4 тыс.Год назад
Outliers are data the points that deviate noticeably far from other data points in a dataset. They can arise for a variety of causes, including measurement errors, experimental errors, or normal data variance. Outliers can significantly affect statistical analysis since they might distort results and make it challenging to draw reliable conclusions. In statistical analysis, outliers must be cor...
How to Write Mean Median Mode Functions in R
Просмотров 459Год назад
A chunk of code known as a function only executes when it is invoked. In R, a function is a reusable piece of code that performs a specific task. Functions are defined using the function() keyword and can take zero or more arguments. Here are some tips for writing functions in R: 1. Define the inputs and outputs of your function clearly 2. Use descriptive variable names 3. Break complex tasks d...
Importance of Statistics | National Statistics Day 2023 | Department of Statistics, BRUR
Просмотров 112Год назад
Statistics is a crucial topic of study since it enables us to comprehend the broad trends and patterns in a particular data collection. Data analysis and inference from it may both be done using a Statistics. Making forecasts about upcoming events and behaviour is another application for it. It keeps us up to date on what is going on in the globe. Because we now live in a world where informatio...
Calculating Descriptive Statistics in Excel | Part 1
Просмотров 95Год назад
The fundamental characteristics of a dataset identified in a particular study are described, illustrated, and summarized using descriptive statistics. The summary provides details on the data sample and its measurements. That makes it easier for analysts to comprehend the data. #descriptive statistics #Excel #Microsoft Excel
Frequency Distribution & Histogram in Excel
Просмотров 436Год назад
Frequency Distribution & Histogram in Excel
How To Create Histogram and Boxplot in R
Просмотров 6992 года назад
How To Create Histogram and Boxplot in R
Create Text file using MS Excel & Read in R
Просмотров 5842 года назад
Create Text file using MS Excel & Read in R
Simple & Multiple Linear Regression Model in R
Просмотров 2102 года назад
Simple & Multiple Linear Regression Model in R
How To Input Data Manually In R and Create Data Frame
Просмотров 7 тыс.2 года назад
How To Input Data Manually In R and Create Data Frame
How To Construct Frequency Distribution Table in R
Просмотров 8 тыс.2 года назад
How To Construct Frequency Distribution Table in R
How To Read Excel Files (CSV, XLSX, XLS) in R
Просмотров 2,2 тыс.2 года назад
How To Read Excel Files (CSV, XLSX, XLS) in R
How To Input Matrix in R | Matrix Operation
Просмотров 4812 года назад
How To Input Matrix in R | Matrix Operation
How to download R and RStudio and install easily
Просмотров 2332 года назад
How to download R and RStudio and install easily
Tnks for the tutorial, it's very helpful ❤
Great thanks for your clear and very informative tutor.❤
Hindi bolla lodu
Hello Arman, thank you for this
why didn't you test a single variable using 3 methods? these results are not comparable and does not explain when to perform what.
Thank you for your query. Each method have their own assumptions and criterion to apply. You can apply boxplot and z score to single variable but not cooks distance. In this tutorial, I tried to show how to use these methods in R. To know more, you have to learn the theory. Thank you.
Simple and easy 👍
Thank you 😊
Thankyou !
thank you, I could not figure out how to do this, I watched so many other videos and looked at so many websites, this is the only video that helped thank you!! I truly appreciate it
We have also essential to calculate R square, adjusted R square, regression model, ANOVA etc. in R. So, we want to get a tutorial in this topic
Check out the uploaded tutorials. You will find all. Wait for ANOVA
So much helpful🤍
Vai❤
😂 P r o m o S M
how can I put my own data in R to make a stem and leaf plot?
There is a separate tutorial for putting data manually in R. You can find it in my channel videos
goooooooooood, that's what I needed
Informative video.Thank you
😊
Thanks for your effective video, vaiya
Very easy and informative video. Keep the good work.
Thanks for the video! I am currently having trouble genenerating truth Tables in the latest version of R studio. Any tips please?
Many thanks to you.
Thank you so much.Keep up this work.
Thanks 💜
Thank you so much
Thanks
Go ahead ❤️❤️❤️
Thanks❤️❤️❤️
I learn here very easily.Thank you so much Arman
Thanks Milon💜
Very helpful for us.
Thanks for your feedback.
Good job! But there is a problem in matrix multiplication.
Could you please mention the problem you found in matrix multiplication?
gd job
Thanks❤️
Nice video
Thanks❤️