At 5% significance level, is there evidence of a linear relationship between shelf space and sales? (use t-test for correlation coefficient) d. Determine the least square regression equation for this data.

At 5% significance level, is there evidence of a linear relationship between shelf space and sales? (use t-test for correlation coefficient) d. Determine the least square regression equation for this data.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

What is the relationship between the amount spent per week on food and the size of the family? Do large families spend more on food? A sample of 10 families in the urban area revealed the following figures for family size and the amount spent on food per week. d. Determine the regression equation. e. Can we conclude that there is a positive association between the amount spent on food and the family size? Use the 0.05 significance level. f. Estimate the amount spent on food per week for a family size 7.
The data from the table below gives a regression that is a) reliable. b) unreliable. c) unable to determine the reliability.
Write the formula for the estimated regression line and interpret the slope of the estimated regression line, the intercept of the estimated regression line- Is it meaningful?, and the estimated R2. Based on the fitted regression model, what is the predicted ATST for a child who is 7 years old? What is the correlation between AGE and ATST? Does the residual plot suggest that the fitted regression line is inappropriate for these data? Explain why or why not. Suppose that a new subject is added to the study data and that subject is 12.5 years old with an ATST of 580 minutes. If the regression model were to be refit with this additional data point, would the new slope be greater than or less than -14.041? Justify your response.
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that there is a positive linear relationship between y and x. True or false?
It is evaluated that there is a relationship between working experience in the business (X) and the number of daily errors (Y). Data are given below. What is the Regression Mean Square of Departure (RAKO) in the validity of the regression model?
Personal wealth tends to increase with age as older individuals have had more opportunitiesto earn and invest than younger individuals. The following data were obtained from a randomsample of eight individuals and records their total wealth (Y) and their current age (X). See attachment for table with figures State the estimated regression line and interpret the slope coefficient.b. What is the estimated total personal wealth when a person is 50 years old?c. What is the value of the coefficient of determination? Interpret it.d. Test whether there is a significant relationship between wealth and age at the 10%significance level. Perform the test using the following six steps.Step 1. Statement of the hypotheses Step 2. Standardised test statistic Step 3. Level of significance Step 4. Decision Rule
Suppose you wanted to test whether or not the payoff to an additional year of education was the same for men and women in the STEM majors. How would you set up your regression analysis in this case
The accompanying Credit Approval Decisions data provide information on credit history for a sample of banking customers. Use regression analysis to identify the best model for predicting the credit score as a function of the other numerical variables, using both the p-value and t-statistic criteria. How do the models compare? Which would you choose? Use a level of significance of 0.05. E Click the icon to view the Credit Approval Decisions data. i........ Credit approval decisions data table ..... What is the best model using the p-value criteria? Select the best answer below and fill in the answer boxes to complete your choice. (Type integers or decimals rounded to three decimal places as needed.) Revolving Utilization (%) Credit Score Years of Credit Revolving Balance (S) History O A. Credit Score = ) Years + (O Balance 728 21 11,420 0.23 VB. Credit Score = 760.800 + (- 219.013) Utilization 576 8 7,300 0.71 680 13 20,100 0.52 O C. Credit Score = O Balance 628 17 12,900 0.68 530 10…
The President of the Farmers Association wants to know how the amount of fertilizer and theamount of water given to plants affect their growth. The results were inputted into MINITABso as to fit the model.Regression Analysis: Growth versus Water, FertilizerThe regression equation isGrowth = ? + ? Water + ?FertilizerPredictor Coef SE Coef T PConstant 42.085 ** 3.118 0.009Water 0.178 0.386 0.460 0.654Fertilizer 5.790 0.952 6.083 *S = 6.159 R-Sq = 77.1%% R-Sq(adj) = 73.3%Analysis of VarianceSource DF SS MS F PRegression 2 1532.603 766.301 *** ****Residual Error 12 455.130 37.928Total 14 1987.733iv. Conduct a hypothesis test, at the 5% level of significance, to determine whether ? issignificant. [4]v. What would be the growth of the plant if 4g of fertilizer and 7g of ater was given to it
B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…
We recorded the pre-statistics course grade (in percent) and introductory statistics course grade (in percent) for 60 community college students. In this data set, no one earned a 90% for the pre-statistics course grade. How could you estimate a student’s introductory statistics course grade if she earned 90% for the pre-statistics course grade? A. Substitute 90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(90) . B. Substitute the decimal 0.90 into the regression equation: Predicted introductory statistics course grade = -0.147 + 0.981(0.90).