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DEMO CLASS: [ক্লিক করে দেখে নিন কোর্সের ডেমো ক্লাসগুলো]
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Demo Class 1: Making a Clustered Bar Chart in SPSS
05:05
Demo Class 2: Calculate Mean, Median, Mode, Standard Deviation in SPSS
02:05
Demo Class 3: One Way ANOVA in SPSS
05:16
Module 1: Getting Started with SPSS
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Know Your Instructor
00:36
Lecture 1: Introduction to SPSS and Its Applications
05:37
Lecture 2: Installing SPSS
06:33
Lecture 3: Understanding the SPSS Interface
02:23
Lecture 4: Creating Data Files
03:24
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Module 2: Data Entry and its Management
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Lecture 1: Data entry manually
13:13
Lecture 2: Import Excel Data into SPSS
03:03
Lecture 3: Excel coding for SPSS
08:03
Lecture 4: Defining and Labeling Variables
04:09
Lecture 5: Opening Data Files and Saving
03:52
Resource (Download)
Module 3: Data Cleaning and Manipulation
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Lecture 1: Identifying Missing Data
01:54
Lecture 2: Managing Missing Data
02:19
Lecture 3: Manipulate Missing Data manually
03:12
Lecture 4: Manipulate Missing data using Smean
04:22
Lecture 5: Understanding missing data for interpretation
09:20
Lecture 6: Generate missing data table for interpretation
03:06
Lecture 7: Interpreting missing data in your research
03:48
Lecture 8: Explaining Outliers
03:08
Lecture 9: Detect Outliers using descriptive statistics
03:21
Lecture 10: Detect Outliers using Boxplots
04:36
Lecture 11: Detect Outliers using Z-scores
04:01
Lecture 12: Interpreting outliers value in your research
07:14
Resource (Download)
Module 4: Data visualization
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Lecture 1: Introduction to Data Visualization
06:00
Lecture 2: Accessing Graphs in SPSS part 1
04:23
Lecture 3: Accessing Graphs in SPSS part 2
02:42
Lecture 4: Bar chart Simple
07:22
Lecture 5: Bar chart Clustered
05:05
Lecture 6: Pie Chart
05:17
Lecture 7: Stacked Bar Chart
03:21
Lecture 8: Histogram
07:18
Lecture 9: Boxplot
05:02
Lecture 10: Line Chart
05:05
Lecture 11: Error Bar Chart
03:21
Lecture 12: Scatterplot
04:10
Lecture 13: Scatterplot Matrix
04:07
Lecture 14: Multiple Line Chart
03:52
Lecture 15: Customizing Charts
04:43
Lecture 16: Exporting Visual
04:20
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Module 5: Data Transformation and Data Reliability
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Lecture 1: Understand the variable and its item
02:30
Lecture 2: Transpose
01:49
Lecture 3: Sort Cases
03:31
Lecture 4: Select Cases
04:09
Lecture 5: Split Files
03:45
Lecture 6: Visual Binning
06:04
Lecture 7: Computing New Variables
06:10
Lecture 8: Testing for Reliability – Cronbach’s Alpha- Part 1
02:15
Lecture 9: Testing for Reliability – Cronbach’s Alpha- Part 2
02:33
Lecture 10: Testing for Reliability – Cronbach’s Alpha- Part 3
03:03
Resource (Download)
Module 6: Normality and Assumption Testing
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Lecture 1: Skewness and Kurtosis
04:15
Lecture 2: Interpretation Skewness and Kurtosis
05:46
Lecture 3: Common Method Bias CMB
06:21
Lecture 4: CMB using Herman one factor test
06:22
Lecture 5: Interpretation of CMB
02:53
Resource (Download)
Module 7: Descriptive Statistics
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Lecture 1: Mean
05:50
Lecture 2: Median
04:45
Lecture 3: Mode
03:17
Lecture 4: Standard Deviation
05:21
Lecture 5: Calculate Mean, Median, Mode, Standard Deviation
02:04
Lecture 6: Frequency test for the variables
02:26
Lecture 7: Interpret frequency
03:00
Lecture 8: Cross Tabulation
03:18
Lecture 9: Demographic Data Analysis part 1
02:52
Lecture 10: Demographic Data Analysis part 2
03:28
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Module 8: Hypothesis Testing/Comparative Statistical Tests (t-tests)
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Lecture 1: Must Know Before Running Any t Test
10:26
Lecture 2: Choosing the Correct t Test
09:34
Lecture 3: Assumptions for t Tests
05:36
Lecture 4: One Sample t Test
07:29
Lecture 5: Independent Samples t Test
08:39
Lecture 6: Paired Samples t Test
05:11
Resource (Download)
Module 9: Correlation and Association
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Lecture 1: Intorduction
06:06
Lecture 2: Pearson Correlation Part 1
06:05
Lecture 3: Pearson Correlation (Part 2)
06:43
Lecture 4: Spearman Correlation
05:05
Lecture 5: Chi Square Goodness of Fit Test
07:22
Lecture 6: Chi Square Test for Independence
06:47
Resource (Download)
Module 10: Regression Analysis
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Lecture 1: Introduction
04:01
Lecture 2: Simple Linear Regression
07:34
Lecture 3: Multiple Linear Regression
06:55
Lecture 4: Model Summary
10:36
Lecture 5: Anova, Coefficient Table
10:42
Lecture 6: Histogram of Residuals, Standardized Residuals
06:27
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Module 11: ANOVA and Non-Parametric Tests
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Lecture 1: Introduction
04:22
Lecture 2: One Way ANOVA
05:16
Lecture 3: One Way ANOVA Interpretation
12:23
Lecture 4: Two way ANOVA
05:51
Lecture 5: Two way ANOVA Interpretaion
08:09
Resource (Download)
Module 12: Survey Techniques
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Lecture 1: Understand Survey Questionnaire
10:22
Lecture 2: Survey Using Google Form
29:28
Module 13: Use of Artificial Inteligence (AI) in SPSS
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AI Utilization in SPSS
07:40
Project: Executing A Quantitative Research Study Using SPSS Analysis
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Executing A Quantitative Research Study Using SPSS Analysis
21:47
Resource (Download)
SPSS Complete Course for Research & Data Analysis
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