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Data Analytics

380 learners

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.

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4 lessons

15 practices

2 hours

Mathematics and Statistics

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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