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Data Analysis 101 with R
Hypothesis Testing in R
Hypothesis Testing in R
Gain proficiency in hypothesis testing within the R environment. Learn to formulate, execute, and interpret various statistical tests to make data-driven decisions.
Lessons and practices
Lesson 1: Mastering Hypothesis Testing with R: Understanding and Performing T-tests
Assessing Impact on Meeting Hours with T-test in R
Adjusting Sample Mean to Test Hypotheses in R
Analyzing Team Efficiency with T-Tests in R
Determining Significance in Remote Working Hours with T-test
Lesson 2: Mastering Non-Parametric Testing: The Mann-Whitney U Test in R
Comparing Website Interaction Times Using Mann-Whitney U Test in R
Interpreting the Mann-Whitney U Test in R
Adjusting Data for Significant Mann-Whitney U Test Results in R
Performing the Mann-Whitney U Test in R
Lesson 3: Mastering ANOVA in R: Analyzing Variance in Grouped Data
One-way ANOVA Test for Apple Weights in R
Adjusting ANOVA Parameters to Achieve Statistical Significance
Analyze Apple Sweetness with One-way ANOVA in R
Lesson 4: Mastering the Chi-Square Test in R: From Theory to Practice
Chi-Square Test for Candy Color Preferences
Chi-Square Test for Unequal Candy Color Preferences
Calculating Expected Frequencies for Chi-Square Test in R
Chi-Square Test for Color Preferences
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