Can too much screen me affect our weight? A researcher, studying the relationship between men screen time spent watching
Posted: Wed May 04, 2022 11:58 am
Can too much screen me affect our weight? A researcher, studying the relationship between men screen time spent watching the at home, work or school) and weight loss per week (gram), collected the following data from weightwatchers club members imple Scree Time in Weight Lossk 500 830 2,000 270 1,200 1,700 800 1,500 380 2.300 130 1,000 470 To save computational time, you may use the following sums, sums of squares and sum of cross-products for subsequent calculations: Ex = 11,000 Ey=3,330 SSxx = 2,635,000 SSyy = 341,987.5 SSxy=-887,750 a. In the least square line ý= a + bx for predicting the Weight Loss/week (y) as a function of Screen Time/week (x), which of the following is the correct value of b (slope)? 340 290 620
calculations: Ex-11,000 Ey-3,330 55xx-2,635,000 5Syy-341,987.5 55xy 187.750 a. In the least square line y-a+bx for predicting the Weight Loss/week (y) as a function of Screen Time/week (x), which of the following is the correct value of b (slope)? ---0.34 Ⓒ044 0.34 O 0.44 b. In the least square line ya + bx, which of the following is the correct value of a (y-intercept)? Ⓒ863.75 O883.75 O-883.75 933.75 c. With the exact values of a and b selected in part (a) and (b) above, use the least square regression line ya + bx to predict "Weight Loss/week" if the "Screen Time/week" is 900. (Note: Enter the numerical value without the unit of measurement rounded to 2 decimal places of accuracy.) Number
OWEN With the exact yahs of and b selected in part tas and there, the last square regression to pr Weight Loss/week it the "Screen Time'week" is 900 (Note: Enter the numerical value without the unit of moment unded to 2 decimal places of accuracy) Number d. Compute the linear correlation coefficient (r) between "Weight Loss/week ( and Screen Timerweek (x) (Note: Enter the numerical value rounded to 4 decimal places of accuracy.) Number e. Approximately what percent of the variation in Weight Loss/week' is explained by its linear relationship with Screen Time/week" (Note: Enter the nearest whole number percentage value without the percent sign.) Number 96 f. Test at a 0.1 level of significance whether the correlation coefficient p is negative. Complete the table below, round Critical Value, and Test Statistic Value to three decimals. Hypotheses B:p 0, Hip 0 Critical Value of t Number Test Statistic Value Number Reject HO? Enter 1 if you 431
(Note: Enter the numerical vidur without the a Numbe & Compute the linear correlation coefficient (r) berwen"Wight Land Time Approximately what percent of the variation in Weight Loss/week' is explained by its linear rannship with Screen Time/week? (Note: Enter the nearest whole number percentage value without the percent sign.) Number 9 f. Test at a 0.1 level of significance whether the correlation coefficient p is negative. Complete the table below, round Critical Value, and Test Statistic Value to three decimals Hypotheses HO:p-0, Hp<0 Critical Value of t Number Test Statistic Value Number Reject Ho Enter 1 if you reject, enter 2 otherwise.) 557
calculations: Ex-11,000 Ey-3,330 55xx-2,635,000 5Syy-341,987.5 55xy 187.750 a. In the least square line y-a+bx for predicting the Weight Loss/week (y) as a function of Screen Time/week (x), which of the following is the correct value of b (slope)? ---0.34 Ⓒ044 0.34 O 0.44 b. In the least square line ya + bx, which of the following is the correct value of a (y-intercept)? Ⓒ863.75 O883.75 O-883.75 933.75 c. With the exact values of a and b selected in part (a) and (b) above, use the least square regression line ya + bx to predict "Weight Loss/week" if the "Screen Time/week" is 900. (Note: Enter the numerical value without the unit of measurement rounded to 2 decimal places of accuracy.) Number
OWEN With the exact yahs of and b selected in part tas and there, the last square regression to pr Weight Loss/week it the "Screen Time'week" is 900 (Note: Enter the numerical value without the unit of moment unded to 2 decimal places of accuracy) Number d. Compute the linear correlation coefficient (r) between "Weight Loss/week ( and Screen Timerweek (x) (Note: Enter the numerical value rounded to 4 decimal places of accuracy.) Number e. Approximately what percent of the variation in Weight Loss/week' is explained by its linear relationship with Screen Time/week" (Note: Enter the nearest whole number percentage value without the percent sign.) Number 96 f. Test at a 0.1 level of significance whether the correlation coefficient p is negative. Complete the table below, round Critical Value, and Test Statistic Value to three decimals. Hypotheses B:p 0, Hip 0 Critical Value of t Number Test Statistic Value Number Reject HO? Enter 1 if you 431
(Note: Enter the numerical vidur without the a Numbe & Compute the linear correlation coefficient (r) berwen"Wight Land Time Approximately what percent of the variation in Weight Loss/week' is explained by its linear rannship with Screen Time/week? (Note: Enter the nearest whole number percentage value without the percent sign.) Number 9 f. Test at a 0.1 level of significance whether the correlation coefficient p is negative. Complete the table below, round Critical Value, and Test Statistic Value to three decimals Hypotheses HO:p-0, Hp<0 Critical Value of t Number Test Statistic Value Number Reject Ho Enter 1 if you reject, enter 2 otherwise.) 557