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What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on
What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 9 women are shown in the table below.
Time | 20 | 88 | 14 | 48 | 51 | 17 | 18 | 40 | 87 |
---|---|---|---|---|---|---|---|---|---|
Pounds | 108 | 148 | 94 | 117 | 148 | 122 | 103 | 134 | 164 |
- Find the correlation coefficient: r=r= Round to 2 decimal places.
- The null and alternative hypotheses for correlation are: H0:H0: ? r == 0 H1:H1: ? r 0 The p-value is: (Round to four decimal places)
- Use a level of significance of=0.05=0.05to state the conclusion of the hypothesis test in the context of the study.
- r2r2= (Round to two decimal places)
- Interpretr2r2:
- The equation of the linear regression line is: yy^ = + xx (Please show your answers to two decimal places)
- Use the model to predict the weight of a woman who spends 55 minutes on the phone. Weight = (Please round your answer to the nearest whole number.)
- Interpret the slope of the regression line in the context of the question:
- Interpret the y-intercept in the context of the question:
- The average woman's weight is predicted to be 96.
- The best prediction for the weight of a woman who does not spend any time talking on the phone is 96 pounds.
- The y-intercept has no practical meaning for this study.
- If a woman does not spend any time talking on the phone, then that woman will weigh 96 pounds.
- The slope has no practical meaning since you cannot predict a women's weight.
- As x goes up, y goes up.
- For every additional minute women spend on the phone, they tend to weigh on averge 0.71 additional pounds.
- Given any group of women who all weight the same amount, 77% of all of these women will weigh the predicted amount.
- There is a large variation in women's weight, but if you only look at women with a fixed weight, this variation on average is reduced by 77%.
- 77% of all women will have the average weight.
- There is a 77% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone.
- There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.
- There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate.
- There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful.
- There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.
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