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the outlier 73
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Добавлен 22 фев 2021
How to perform Principal component Analysis (PCA) on LIKERT SCALE ITEMS for QUESTIONNAIRE using SPSS
In this video, we'll guide you through the step-by-step process of conducting Principal Component Analysis (PCA) on Likert scale items in a questionnaire using SPSS. This tutorial is perfect for research scholars looking to simplify complex data into meaningful components.
Key Highlights:
- Kaiser-Meyer-Olkin (KMO) Measure: Understand the importance of checking sampling adequacy to ensure PCA is appropriate for your data.
- Bartlett's Test of Sphericity: Learn how to test whether your data's correlation matrix is suitable for PCA.
- Eigenvalue and the K1 Rule: Discover how to determine the number of components to retain using the eigenvalue-greater-than-one rule.
- Rotation (Varimax): See how ...
Key Highlights:
- Kaiser-Meyer-Olkin (KMO) Measure: Understand the importance of checking sampling adequacy to ensure PCA is appropriate for your data.
- Bartlett's Test of Sphericity: Learn how to test whether your data's correlation matrix is suitable for PCA.
- Eigenvalue and the K1 Rule: Discover how to determine the number of components to retain using the eigenvalue-greater-than-one rule.
- Rotation (Varimax): See how ...
Просмотров: 1 285
Видео
How to Calculate Z-Scores for SCALE variables in SPSS: A Step-by-Step Guide for Beginners
Просмотров 1884 месяца назад
Z-Score: Overview What is a Z-Score? - A Z-score (or standard score) represents the number of standard deviations a data point is from the mean of a dataset. - It is a measure of how far and in what direction a single data point deviates from the mean. Applications of Z-Scores: 1. Standardizing Data: - Z-scores standardize different datasets, making them comparable by putting them on the same s...
LIKERT SCALE analysis and interpretation using Descriptive Statistics (FREQUENCY and PERCENTAGE)
Просмотров 5044 месяца назад
When analyzing a Likert scale using descriptive statistics, you can summarize the data using frequencies and percentages. This approach helps in understanding the distribution of responses across different scale points. Steps to Analyze and Interpret a Likert Scale 1. Data Collection: Collect responses on a Likert scale (e.g., 1 = Strongly Disagree, 5 = Strongly Agree). 2. Frequency Distributio...
Simplify Your Research: How to create a Codebook for LIKERT SCALE ITEMS in SPSS
Просмотров 2164 месяца назад
Are you looking to streamline your research process? In this video, we'll walk you through the step-by-step process of creating a codebook in SPSS, an essential tool for organizing and understanding your data. Whether you're a beginner or an experienced researcher, this tutorial will simplify the process, making it easy to generate a clear and concise codebook for your project. Learn how to doc...
How to Rank Likert Scale Items using SPSS(For Research Scholars, MBA students and PHD Thesis)
Просмотров 1384 месяца назад
In this video, you'll learn how to effectively rank Likert scale items using SPSS. Whether you're a research scholar, MBA student, or working on your PhD thesis, this guide will walk you through the step-by-step process of ranking responses from Likert scales to analyze your survey data. We'll cover key techniques and best practices to ensure accurate and meaningful results. Perfect for anyone ...
How to easily import and automatically recode a 5-point LIKERT SCALE data from EXCEL to SPSS
Просмотров 1054 месяца назад
A step-by-step guide to import, Recode and Analyze 5-point LIKERT SCALE data in SPSS
How to import, code and analyze 5 point LIKERT SCALE ITEMS from Google form into SPSS
Просмотров 3314 месяца назад
To import, code, and analyze Likert scale data from Google Forms into SPSS, follow these steps: 1. Export Data from Google Forms: - After collecting responses, go to the Google Forms Responses tab. - Click on the Google Sheets icon to view the responses in a spreadsheet. - Download the spreadsheet as a .csv file by selecting File -Download Comma Separated Values (.csv). 2. Import Data into SPSS...
How to test the VALIDITY of a 5point LIKERT SCALE QUESTIONNAIRE by using Pearson CORRELATION in SPSS
Просмотров 1 тыс.4 месяца назад
In this video, we will delve into how to use Pearson's correlation method to assess the validity of Likert scale questionnaires in SPSS. Designed specifically for research scholars and PhD students, this comprehensive guide will provide you with the tools to enhance the accuracy and reliability of your research data. You will learn: - How to calculate Pearson's correlation coefficient to explor...
How to increase CRONBACH ALPHA: RELIABILITY ANALYSIS on 5-Point LIKERT SCALE (For Research Scholars)
Просмотров 2714 месяца назад
Welcome to our channel! 📊 In this video, we'll guide you through a simple and effective method for performing reliability analysis using Cronbach's Alpha on a 5-point Likert scale. Whether you're a research scholar, student, or professional, this tutorial is designed to help you understand and improve the reliability of your data. 🌟 What You'll Learn: 1. What is Reliability Analysis? - Explanat...
How to analyze 5-point LIKERT SCALE in SPSS and INTERPRET the results in word-For Research Scholars
Просмотров 8484 месяца назад
Analyzing and interpreting Likert scale data can be done using various methods. Here are three common approaches: Descriptive Statistics: - Mean and Standard Deviation: Though controversial, the mean can sometimes be used if you assume the intervals between points are approximately equal. The standard deviation can provide insight into the variability of responses. - Median and Mode: More appro...
SPSS Graphs: How to create scatterplots in SPSS
Просмотров 1255 месяцев назад
Unlock the power of scatterplots in SPSS with this step-by-step guide! Scatterplots are essential for visualizing the relationship between two variables, helping you uncover patterns and correlations in your data. Whether you're new to SPSS or looking to refine your graphing skills, this tutorial will help you master scatterplot creation.
Transform Your Data: Step-by-Step Variable Recoding in SPSS
Просмотров 1275 месяцев назад
Unlock the power of SPSS with our comprehensive guide to variable recoding! Whether you're a beginner or looking to refine your skills, this video walks you through each step of the recoding process in SPSS. Learn how to transform your data efficiently and accurately with easy-to-follow instructions and practical examples. In this video, you will discover: - The basics of variable recoding and ...
Step by Step guide to Principal Component analysis (PCA) in SPSS
Просмотров 4125 месяцев назад
Welcome to our comprehensive guide on Principal Component Analysis (PCA) using SPSS. In this tutorial, we'll walk you through the entire process, from loading your wholesale price index data to interpreting the final results. You'll learn how to perform PCA, create and analyze scree plots, and build path diagrams. Whether you're a beginner or looking to refine your skills, this step-by-step gui...
1992 Presidential Election Data Analysis: Chi-Square & CHAID Decision Trees
Просмотров 1285 месяцев назад
Welcome to our deep dive into the fascinating world of election data analysis! 📊 In this video, we explore the 1992 Presidential Election dataset using advanced statistical techniques and decision tree analysis. Join us as we: 1. Perform an Exploratory Data Analysis (EDA) to uncover hidden patterns and trends. 2. Use the Chi-Square test to analyze the relationship between categorical variables....
SPSS Graphs for Beginners: Pie Chart, Bar chart and Histogram with Normal Curve
Просмотров 2496 месяцев назад
SPSS Graphs for Beginners: Pie Chart, Bar chart and Histogram with Normal Curve
Reliability Analysis: Comparing Cronbach's Alpha and Guttman's Split-Half Coefficient
Просмотров 3416 месяцев назад
Reliability Analysis: Comparing Cronbach's Alpha and Guttman's Split-Half Coefficient
SPSS Graphs Made Easy: Pie Charts, Clustered Boxplots, Scatterplots, SPLOM, and Heatmaps
Просмотров 4676 месяцев назад
SPSS Graphs Made Easy: Pie Charts, Clustered Boxplots, Scatterplots, SPLOM, and Heatmaps
SPSS Graphs Made Easy: Bar Charts, Stacked Bar Charts, Histograms, Dot Plots, Boxplot(For Beginners)
Просмотров 1156 месяцев назад
SPSS Graphs Made Easy: Bar Charts, Stacked Bar Charts, Histograms, Dot Plots, Boxplot(For Beginners)
Predicting Loan Defaults with QUEST: A Step-by-Step Guide
Просмотров 1016 месяцев назад
Predicting Loan Defaults with QUEST: A Step-by-Step Guide
Karnataka Disability Data with SPSS: Hierarchical cluster analysis, Dendrogram, Tree Custom Tables
Просмотров 546 месяцев назад
Karnataka Disability Data with SPSS: Hierarchical cluster analysis, Dendrogram, Tree Custom Tables
Robust Statistical Modeling with M-Estimators in SPSS (For Advanced SPSS users)
Просмотров 1956 месяцев назад
Robust Statistical Modeling with M-Estimators in SPSS (For Advanced SPSS users)
Missing Value Analysis using MCMC (Markov Chain Monte Carlo) Simulation and Bayesian Inference.
Просмотров 2146 месяцев назад
Missing Value Analysis using MCMC (Markov Chain Monte Carlo) Simulation and Bayesian Inference.
Bank Loan Default Prediction: CART Model in SPSS with 5-Fold Cross Validation
Просмотров 1596 месяцев назад
Bank Loan Default Prediction: CART Model in SPSS with 5-Fold Cross Validation
Big or Small, Protect Them All: Help Us Understand Breast Cancer
Просмотров 266 месяцев назад
Big or Small, Protect Them All: Help Us Understand Breast Cancer
How to Create a Population Pyramid Chart in SPSS | Step-by-Step Tutorial
Просмотров 4156 месяцев назад
How to Create a Population Pyramid Chart in SPSS | Step-by-Step Tutorial
Ch1: How to import a Excel File in SPSS for Beginners
Просмотров 716 месяцев назад
Ch1: How to import a Excel File in SPSS for Beginners
SPSS Transform Menu Compute variable| SPSS for Beginners: Creating New Variables from Existing Data
Просмотров 1196 месяцев назад
SPSS Transform Menu Compute variable| SPSS for Beginners: Creating New Variables from Existing Data
Forward Selection Explained: Linear Regression with Boston Housing Dataset
Просмотров 1527 месяцев назад
Forward Selection Explained: Linear Regression with Boston Housing Dataset
Thank you so much sir.this vedio released my strees. Thank you again.
Glad you liked it, ALL the best
In rotated components matrix, do we need to consider negative values ? Like -0.856
yes you need to consider
The magnitude (absolute value) of the loading indicates the strength of the relationship between the variable and the factor, regardless of whether it's positive or negative.
@@theoutlier7395 ok thanks for replying
thank you for clear explanation!!! It is very useful!
Glad you found it useful, All the best
amazing video. helped a lot to do analysis for my research. god bless you
Thnaks all the best
Thanks
Best wishes
grant me access request
Thanks. I have got the main point of the course from Ur presentation.
gllad it helped you
very niccely explained
But i am not able to see this option of Analyze in my Power BI desktop discussed at 16.33.
Thanks Glad you liked it
Grant my request
Dataset
please make a video on the installation of jupyter and seaborn
slightly busy these days with other things, Will do once i find time
🎉❤
Sir, can you share me data set
kindly send the request one again il be able to share. old request is not active
@@theoutlier7395 thank you very much
Sir , please grant me access request Thankss :)
Granted
kindly share request old request is not active
sir, my research is similar to yours. i am researching about sensory test for 30 panelists and there is 5 samples. i followed literally all of your tutorial including make the panelists is the variables. but why it said that my correlation matrix "non-positive defini te matrix"?
looks like your sample size is very small. at least 100?
typically 1:20, for every variable 20 records
Sir, how did you made the heat map ?
Excel
Can you help me Integratinh fuzzy Values & can i use this in Computing most critical safety risk factors
sir i have sent you the request to download data set.. Kindly approve the same
have done it
Nice
Thanks
can you provide me this dataset
please share ur mail id i will share the file
Sir i removed variables to increase cronbuch alpha value, still this value not improved after .699. is it any other option to boost cronbuch alpha value.
.699 is a good value. Dont need to improve any further
if u still want to improve you can again drop one more item which is bringing down the alpha as per the video
Sir if removed variables whose affected reliability test , so it means we can't use these variables in result analysis of study.
once you drop variables u cant use them further
Sir in my study have non metric data, I want to apply multivariate analysis, is it PCM method appropriate for it. 1. If not what method appropriate for it. 2. I have socio and economic section related many variables.
If you have Ordinal(5 point scale) you can still go ahead and use PCA
Pl. Note: Since you have non-metric data, Principal Component Analysis (PCA) might not be the best method. PCA is typically used for metric data (interval or ratio) because it relies on variances and covariances, which aren't meaningful for categorical data.
Try Multiple Correspondence Analysis (MCA) or f actor Analysis for Mixed Data (FAMD)
Thank you so much sir for your response 🙏🙏
@@neelamkhanoda6252 All the best
Really nice! Can you please tell how to watch the videos which are meant for members only? Is there any membership option?
Thanks, Will let you know in a bit
Sir, in first method, in total column my values are less than 0.05 for all variables, but in other column in some variables significant value are greater than 0.05. is my questionnaire is validation or not
madam if the correlation with total colum is gretaer than 0.05 it implies questionnaire is invalid
Sir correlation with total column is less than 0.05
@@theoutlier7395thank you sir for your response, your videos really help me a lot 🙏🙏🙏
Glad it does, All the best
@@neelamkhanoda6252 Please look at the sig. value of each variable with the total column
Hello sir non it se hu kya only power bi Se job ho sakti h
Hi Ravi, For first one or two years work in Power bi and Tableau. once you understand the analytics space Please change job after 1 or 1.5 years
Hi Ravi, Aap Power Bi Tableau SQL se bhi start kar sakthei hain
7:35 Why did you select the absolute value as 0.6?
if the factor loading is lesser than 0.6, we neglect it.
How to choose excel in new query
usually once you click New Query option, please note under the ODBC Data sources section the Excel option will be displayed. Which you can click to select Excel option. If Excel is not getting displayed please click Add ODBC Data source and enable ODBC drivers for excel. Then Excel option will be displayed. which you can use to import.
Sir, I have to create an index (weighted). Can I assign weight through PLA to different components based on their importance? Please give some steps for this
Multiply the original variables by their corresponding component scores (from the PCA loadings). Sum the weighted scores to obtain the final index.
Is it ok to consider the item belongs to that component where the item itself indicates higher loading
yes those items have a high loading you can consider rest please ignore
Hello, sir; it was highly informative. Do you have any video about how to write interpretation with Decission Tree analysis? how do we ave to add image from SPSS etc.
in future i will make videos for this.
Thanks for the video! Is there a way to change the bins so that the last bin contains everything not contained in the other bins?
not easy to to do that
Can you also provide the best answers to answer these questions
hell yea brother!!!! thanks for showing me how to lay out my pivot table and walking me through the calculations!!!!
thanks Glad it helped
Your clip is very clear, thanks!!
thanks
I have 7 variables, and 37 items, while performing PCA analysis, fixed number of factor ( how many should i keep, 7 or should i leave it empty for software to decide?
Let the sofware decide
Thank you so much.
All the best
Hi I got a value of log price in mine as -3.1 what does this mean?
hi, The log value -3.1 means that the price is significantly less than 1. This is because, on a logarithmic scale, negative values correspond to numbers between 0 and 1.
Just a few questions. While fitting a decision tree, isn't a node split into two nodes only? Here, specifically for medium income group, with respect to age, the node has been split into four nodes, instead of two. Also, the two terminal nodes at the extreme left provide the same value of the dependent variable, which is "Bad" credit risk, following the majority class rule. But weren't the two nodes supposed to provide two different values of the dependent variable? Otherwise these terminal nodes would not have been created since they are not providing any different prediction from the node from which they got created (because the goodness of split value is low for the mother node here). Same goes for the terminal nodes at extreme right. Is all this due to the CHAID algorithm being used here?
CART model supports binary splits. however chaid supports multiple splits