For the regression equation Y = 2X-1, if the mean for X is Mx = 8, what is the mean for Y? 07 O 15 4.5 Impossible to determine.
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A: Given: x: hours of TV watches y: number of sit-ups y=ax+ba=-1.357b=20.532
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A: A regression was run to determine if there is a relationship between hours of TV watched per day,x,…
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A: Given that the regression equation is, y=ax+b b=31.768 a=-1.128 Therefore, y=-1.128x+31.768
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- A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.The mall has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents(Y). Analysis on the set finds that the regression equation is Y=100-3X. What is the likely number of accidents for someone aged 30? 97 100 10 none of the aboveHow do we do in excel
- A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy).The results of the regression were: y=ax+b a=-0.904 b=24.378 r2=0.64 r=-0.8 Use this to predict the number of sit ups a person who watches 9.5 hours of TV can do, and please round your answer to a whole number.Please all the 3 of these sub-questions. Make sure answer is rounded up to 4 decimalsHoly...I’m stuck on these. I really don’t know how to do them. I added a picture of the questions
- You may need to use the appropriate technology to answer this question. A regression analysis involving 45 observations relating a dependent variable and two independent variables resulted in the following information. ý = 0.406 + 1.3385X, + 2X2 The SSE for the above model is 43. When two other independent variables were added to the model, the following information was provided. ý = 1.9 – 3X + 12X2 + 4Xg + 8x, This model's SSE is 36. At a 0.05 level of significance, test to determine if the two added independent variables contribute significantly to the model. State the relevant null and alternative hypotheses. O Ho: One or more of the parameters is not equal to zero. H₂: B₁ = B₂= B3 =B4 = 0 O Ho: One or more of the parameters is not equal to zero. H₂: B3 =B4 = 0 O Ho: B3 = P4 = 0 H₂: None of the parameters are equal to zero. ⒸH₁: B3 =B₁ = 0 H: One or more of the parameters is not equal to zero. O Ho: B₁ = P₂ = B3 =B4 = 0 H: One or more of the parameters is not equal to zero. ✔ Find…How does R treat those observations with missing values? In other words, what role do the observations with missing values play in the regression? No command is needed for this question. You must need to provide an answer or take a guess.The following table gives the data for the hours students spent on homework and their grades on the first test. The equation of the regression line for this data is yˆ=43.097+1.15x. This equation is appropriate for making predictions at the 0.01 level of significance. If a student spent 32 hours on their homework, make a prediction for their grade on the first test. Round your prediction to the nearest whole number. Hours Spent on Homework and Test Grades Hours Spent on Homework 30 30 31 42 11 27 34 47 5 29 Grade on Test 83 75 75 96 45 76 97 85 53 75
- The multiple regression describes how the mean value of y is related to the xi independent variables. The parameters ?i are used to describe how the mean value of y changes for a one-unit increase in xi when the other variables are held constant. The given estimated regression equation follows where x1 is the high-school grade point average, x2 is the SAT mathematics score, and y is the final college grade point average. ŷ = −1.38 + 0.0232x1 + 0.00482x2 If the variable x2 is held constant, then only changes in x1 will impact the predicted values of ŷ. Since the coefficient of x1 is positive, for each one-unit increase of x1, the values of ŷ will increase by the value of ?1, where ?1 = . In context, for each one point increase of the high-school grade point average, the final college grade point average will increase by this amount when the SAT mathematics score does not change. If the variable x1 is held constant, then only changes in x2 will impact the predicted values of ŷ. Since the…A regression was run to determine if there is a relationship between hours of TV watched per day, x, and number of sit-ups, y, a person can do in a minute. The results of the regression were: y=ax+b a=-1.255 b=21.239 Use this to predict the number of sit-ups a person who watches 11.5 hours of TV can do in a minute. Round to the nearest whole number.A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y).The results of the regression were: ˆy=-1.278 x+x+31.637r2=0.719104r2r=−0.848 Use this to predict the number of sit ups a person who watches 12 hours of TV can do, and please round your answer to a whole number.
