Please solve only problems that haven’t been answered thank you please circle your answers Question 3What is the relationship between the number of minutes per day a woman spends talking on the phone andthe woman's weight? The time on the phone and weight for 8 women are shown in the table below.Time 18 88 21 65 33Pounds 98 141 119 144 101c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the contextof the study.O There is statistically insignificant evidence to conclude that a woman who spends more timeon the phone will weigh more than a woman who spends less time on the phone.34109O There is statistically insignificant evidence to conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the use of the regression line is notappropriate.O There is statistically significant evidence to conclude that a woman who spends more time onthe phone will weigh more than a woman who spends less time on the phone.d. ² = 0.71(Round to two decimal places)-59There is statistically significant evidence conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the regression line is useful.e. Interpret ²:O There is a large variation in women's weight, but if you only look at women with a fixedweight, this variation on average is reduced by 71%.f. The equation of the linear regression line is:$F45632140 116O Given any group of women who all weight the same amount, 71% of all of these women willweigh the predicted amount.O 71% of all women will have the average weight.There is a 71% chance that the regression line will be a good predictor for women's weightbased on their time spent on the phone.doRound to 2 decimal places.%F5(Please show your answers to two decimal places)F6&F7DIIF8F9 sNF2time women spend on the phone and their weight. Thus, the use of the regression line is notappropriate.There is statistically significant evidence to conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the regression line is useful.O There is statistically significant evidence to conclude that a woman who spends more time onthe phone will weigh more than a woman who spends less time on the phone.d. ²0.71 (Round to two decimal places)e. Interpret ²:O There is a large variation in women's weight, but if you only look at women with a fixedweight, this variation on average is reduced by 71%.#3O Given any group of women who all weight the same amount, 71% of all of these women willweigh the predicted amount.071% of all women will have the average weight.There is a 71% chance that the regression line will be a good predictor for women's weightbased on their time spent on the phone.f. The equation of the linear regression line is:y =g. Use the model to predict the weight of a woman who spends 45 minutes on the phone.Weight =(Please round your answer to the nearest whole number.)h. Interpret the slope of the regression line in the context of the question:O For every additional minute women spend on the phone, they tend to weigh on averge 0.64additional pounds.80F3O As x goes up, y goes up.O The slope has no practical meaning since you cannot predict a women's weight.i. Interpret the y-intercept in the context of the question:O The best prediction for the weight of a woman who does not spend any time talking on thephone is 93 pounds.O The y-intercept has no practical meaning for this study.O The average woman's weight is predicted to be 93.O If a woman does not spend any time talking on the phone, then that woman will weigh 93pounds.$(Please show your answers to two decimal places)48888F4R%5F5TA6F6Y&7AAF7U*8DIIF8(9DDF9)0JF10O PC

Question

Please solve only problems that haven’t been answered  thank you please circle your answers Question 3What is the relationship between the number of minutes per day a woman spends talking on the phone andthe woman's weight? The time on the phone and weight for 8 women are shown in the table below.Time 18 88 21 65 33Pounds 98 141 119 144 101<a. Find the correlation coefficient: r = 0.84b. The null and alternative hypotheses for correlation are:Ho: P = 0H₁: p0The p-value is: 0.00861 (Round to four decimal places)80F3>c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the contextof the study.O There is statistically insignificant evidence to conclude that a woman who spends more timeon the phone will weigh more than a woman who spends less time on the phone.34109O There is statistically insignificant evidence to conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the use of the regression line is notappropriate.O There is statistically significant evidence to conclude that a woman who spends more time onthe phone will weigh more than a woman who spends less time on the phone.d. ² = 0.71(Round to two decimal places)-59There is statistically significant evidence conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the regression line is useful.e. Interpret ²:O There is a large variation in women's weight, but if you only look at women with a fixedweight, this variation on average is reduced by 71%.f. The equation of the linear regression line is:$F45632140 116O Given any group of women who all weight the same amount, 71% of all of these women willweigh the predicted amount.O 71% of all women will have the average weight.There is a 71% chance that the regression line will be a good predictor for women's weightbased on their time spent on the phone.doRound to 2 decimal places.%F5(Please show your answers to two decimal places)F6&F7DIIF8F9 sNF2time women spend on the phone and their weight. Thus, the use of the regression line is notappropriate.There is statistically significant evidence to conclude that there is a correlation between thetime women spend on the phone and their weight. Thus, the regression line is useful.O There is statistically significant evidence to conclude that a woman who spends more time onthe phone will weigh more than a woman who spends less time on the phone.d. ²0.71 (Round to two decimal places)e. Interpret ²:O There is a large variation in women's weight, but if you only look at women with a fixedweight, this variation on average is reduced by 71%.#3O Given any group of women who all weight the same amount, 71% of all of these women willweigh the predicted amount.071% of all women will have the average weight.There is a 71% chance that the regression line will be a good predictor for women's weightbased on their time spent on the phone.f. The equation of the linear regression line is:y =g. Use the model to predict the weight of a woman who spends 45 minutes on the phone.Weight =(Please round your answer to the nearest whole number.)h. Interpret the slope of the regression line in the context of the question:O For every additional minute women spend on the phone, they tend to weigh on averge 0.64additional pounds.80F3O As x goes up, y goes up.O The slope has no practical meaning since you cannot predict a women's weight.i. Interpret the y-intercept in the context of the question:O The best prediction for the weight of a woman who does not spend any time talking on thephone is 93 pounds.O The y-intercept has no practical meaning for this study.O The average woman's weight is predicted to be 93.O If a woman does not spend any time talking on the phone, then that woman will weigh 93pounds.$(Please show your answers to two decimal places)48888F4R%5F5TA6F6Y&7AAF7U*8DIIF8(9DDF9)0JF10O PC

Accepted Answer

Time:X
Pound:Y

18
98

88
141

21
119

65
144

33
101

34
109

56
140

32
116