APPLICATION B: Young women globally appear to be obsessed with weight control, B
ID: 3312635 • Letter: A
Question
APPLICATION B: Young women globally appear to be obsessed with weight control, Being thin has become a multi-billion dollar business. A firm has a product, x113 that supports dieting. Based on this trend, the following Hypothesis 1 is stated: Perceptions that young women are overweight are related negatively to perceptions of attractiveness." A study was concluded that gathered interval data collected from a large sample of women. These data were entered into a SPSS Program with the following results generated Sum of dt MeanSauare 4.914 0.000 Regression Residual Total 9.228 112.660 121.887 60 61 9.227 1.877 REGRESSION Standardized Coefficients e 4636 Unstandardized Coefficients Standard (Constant) 4.414 X113 0.952 0.262 0.000 0.030 -0582 0.275 -2.216 a. Given the information above, is the suggested model (Beauty f(-W.) significant? If significant which statistic is evidence of this and how do you interpret its significance (Hint: Why does/does not the statistic suggest further research? Exactly what contribution to the interpretation of the regression does the Adjusted R'value contribute? What does it explain? b. What evidence exists that the hypothesized relationship is significant/not significant? Explain the statistic that addresses this relationship. Interpret the result. c. Set up the regression equation and calculate the effective of weight loss (Lbs) on beauty enhancement. What is the effect of a 25 pound weight loss on the beauty dimension? d.Explanation / Answer
a) Given suggested model is significant
since p value = 0.000 < 0.05 rejection level
Critical value approach
Decision rule o F statistic : if F statistic < F critical = 4 on (1,60) df at 5% level
Actual decision : F statistic = 4.914 > 4, so reject H0, significant difference
b) Here the coefficient of determination 'r2' = SSR/SST = 9.228/121.887 = 0.076
it indicates only 7.6% variation is accounted of dependent variable on independent
c) significant mean sufficient evidence of reject null hypothesis otherwise alternative
Here F statistic > F critical (mentioned above)
Then there is sufficient evdience of regression model is suitable for prediction
d) Regression equation
Y = 4.414 - 0.0582X
If X = 25, thenY = 4.414 - 0.0582 * 25 = 2.96
d)