Beanie Babies are toy stuffed animals that have become valuable colector's items since the introduction of...

 

Transcribed Image Text:

Beanie Babies are toy stuffed animals that have become valuable colector's items since the introduction of Ally the Alligator in 1994. Beanie World Magazine provided the information on 50 beanie babies which is available in beanie.csv. We are interested in determining if age can be used to accurately predict its market value. The unit for age is month and the unit for value is dollar. (Hint: you only need to focus on variables of age and value.) 1) Plot the scatter diagram of age (x-axis) versus value (y-axis). 2) Calculate the Pearson correlation between age and value. 3) Conduct a simple regression analysis and obtain the least square fit for value (response variable) on age (predictor). 4) Write down the hypotheses (null and alternative) for testing the association between age and value using a linear line. 5) What proportion of the variability in value is explained by the straight regression line? 6) Do the data provide sufficient evidence to indicate that there is a significant association between age and value? (Use type I error at 0.05) 7) Interpret the point estimate of the slope in the fitted linear regression in 3). 8) Find a 95% confidence interval for the slope of Age. 9) What value is predicted if age is 6 years old? 10) Calculate the corresponding prediction interval in question 9). Beanie Babies are toy stuffed animals that have become valuable colector's items since the introduction of Ally the Alligator in 1994. Beanie World Magazine provided the information on 50 beanie babies which is available in beanie.csv. We are interested in determining if age can be used to accurately predict its market value. The unit for age is month and the unit for value is dollar. (Hint: you only need to focus on variables of age and value.) 1) Plot the scatter diagram of age (x-axis) versus value (y-axis). 2) Calculate the Pearson correlation between age and value. 3) Conduct a simple regression analysis and obtain the least square fit for value (response variable) on age (predictor). 4) Write down the hypotheses (null and alternative) for testing the association between age and value using a linear line. 5) What proportion of the variability in value is explained by the straight regression line? 6) Do the data provide sufficient evidence to indicate that there is a significant association between age and value? (Use type I error at 0.05) 7) Interpret the point estimate of the slope in the fitted linear regression in 3). 8) Find a 95% confidence interval for the slope of Age. 9) What value is predicted if age is 6 years old? 10) Calculate the corresponding prediction interval in question 9).