data analysis with r coursera week 3 quiz answers

Practice Quiz

1. When conducting exploratory data analysis, which visualizations are particularly useful for examining the distribution of numerical data and skewness through displaying the data quartiles (or percentiles) and averages?

  • Heatmaps
  • Histograms
  • Boxplots 
  • Scatter plots

2. When grouping data and calculating the mean of each group as part of your exploratory data analysis, you typically use the group_by() function with which other function?

  • sort()
  • desc()
  • summarize()
  • arrange()

3. Which of the following forms of exploratory data analysis is a statistical comparison of groups of data?

  • Analysis of variance (ANOVA)
  • Correlation 
  • Pearson correlation
  • Descriptive statistics

4. Which of the following statements describe a positive correlation between two variables? Select two answers.

  • Both variables move in opposite directions.
  • Both variables move in the same direction. 

  • The correlation coefficient is less than zero.
  • The correlation coefficient is greater than zero.

5. When using the Pearson method to evaluate the correlation between two variables, which set of numbers indicates a strong positive correlation?

  • The correlation coefficient is .85 and the P value is 0.00037.
  • The correlation coefficient is -.85 and the P value is 1.
  • The correlation coefficient is -.85 and the P value is 0.00037.
  • The correlation coefficient is .85 and the P value is 0.06. 

Graded Quiz

6. Which of the following forms of exploratory data analysis generates short summaries about the sample and measures of the data?

  • Pearson correlation
  • Correlation
  • Analysis of variance (ANOVA)
  • Descriptive statistics 

7. When conducting exploratory data analysis, which visualizations are particularly useful for plotting the target variable over multiple variables to get visual clues of the relationship between these variables and the target.

  • Scatter plots
  • Boxplots
  • Histograms
  • Heatmaps

8. Which of the following statements about the ANOVA F-test score are true? Select two answers.

  • A small F-test score implies a strong correlation between variable categories and the target variable.
  • A small F-test score implies a poor correlation between variable categories and the target variable.

  • A large F-test score implies a strong correlation between variable categories and the target variable. 

  • A large F-test score implies a poor correlation between variable categories and the target variable. 

 

9. You can visualize the correlation between two variables by plotting them on a scatter plot and then doing which of the following?

  • Add a regression line.  
  • You should not use a scatter plot for visualizing the correlation between two variables. 
  • Nothing. The scatter plot alone can show the correlation completely.
  • Add a correlation line.

10. When using the Pearson method to evaluate the correlation between two variables, how do you know you can have strong certainty in the result?

  • The P value is less than 0.05.
  • The P value is less than 0.1. 
  • The P value is greater than 0.1. 
  • The P value is less than 0.001. 

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