Assignment 2.3-2.4

# Based on the above output a scatterplot of this data

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13. Based on the above output, a scatterplot of this data set that will be used for prediction purposes would have which variable on which axis? a. Price on X axis, Size on Y axis b. Size on X axis, Price on Y axis c. It doesn’t matter. The regression line won’t change if you switched X and Y d. “Size” variable on the X axis and “Constant” variable on the Y axis 14. What is the equation of the best-fitting regression line? Find this in two ways. First, using the regression analysis part of the output, and then using the descriptive statistics part of the output. 15. For each square foot increase in house size, how much does the price increase (in dollars) on average? Explain your answer. 16. Does the Y-intercept have an interpretation here? Why or why not? Let x be the change in a stock market index in January and let y be the change in the stock market index for the entire year. Descriptive statistics from 1960 to 1997 are shown below. Descriptive Statistics: Jan, Year Total Variable Count Mean StDev Minimum Median Maximum Jan 37 0.018 0.016 0.002 0.020 0.200 Year 37 0.091 0.010 0.520 0.101 0.393 Pearson correlation of Jan and Year = 0.796 P-Value = 0.895 17. You want to use the January change in stock market index (x) to predict the change in the stock market index for the entire year (y). Find the equation of the best-fitting line. *18. Give 2 statistical reasons why you know this relationship is positive. 19. Explain why you think the relationship between X and Y is so strong in this problem (in other words why is the correlation so high?)

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Here are data for calories and salt content (milligrams of sodium) in 17 brands of meat hot dogs: Sodium (mg) Calories 600 500 400 300 200 100 200 180 160 140 120 100 Scatterplot of Calories vs Sodium (mg) 20. A computer found the regression equation for the above problem is Calories = 61.6 + 0.232 Sodium (mg). How do we interpret the slope of this line? a. As the amount of sodium increases by 1 milligram, the calories increase by 0.232 b. As the amount of sodium increases by 1 milligram, the calories increase by 61.6 c. As the amount of calories increases by 1, the sodium increases by 0.232 milligrams d. As the amount of calories increases by 1, the sodium increases by 61.6 milligrams. 21. Interpret the Y-intercept. Does it make sense here? 22. For what range of sodium can you make a good prediction about calories? Suppose the age of a woman is strongly correlated with the age of her husband when both are marrying for the 2nd time. Variable N Mean StDev Min Max Woman’s Age 28 31.24 9.49 17.06 58.97 Husband’s Age 28 35.79 8.86 14.00 51.00 Pearson’s Correlation: 0.9586 23. There is a positive linear relationship between these two variables. Explain why this makes sense in the context of this problem.
*24 . Suppose you want to use the woman’s age to predict her husband’ age. Find the slope of the regression line.

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