2 PART Question regarding MULTIPLE LINEAR REGRESSION A researcher is interested in predicting the number of homes sold from years in business as a real estate agent and their level of education. Part 1- In jamovi explore the relationship between these variables and describe what the results are PART 2 - Conduct the regression analysis in jamovi

2 PART Question regarding MULTIPLE LINEAR REGRESSION A researcher is interested in predicting the number of homes sold from years in business as a real estate agent and their level of education. Part 1- In jamovi explore the relationship between these variables and describe what the results are PART 2 - Conduct the regression analysis in jamovi

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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1. Sue is conducting a regression analysis to predict the amount of salaries expense using the number of employees and the average rate of pay. This type of regression analysis is called a(n) independent regression. linear regression. multiple regression. dependent regression.
can you please help with questions a-e i need help
A statistical program is recommended. Consider the following data for two variables, x and y. 24 26 30 22 35 40 y 13 22 33 34 41 35 (a) Develop an estimated regression equation for the data of the form ŷ = b, + b,x. (Round b, to one decimal place and b, to three decimal places.) (b) Use the results from part (a) to test for a significant relationship between x and y. Use a = 0.05. Find the value of the test statistic. (Round your answer to two decimal places.) F = Find the p-value. (Round your answer to three decimal places.) p-value = Is the relationship between x and y significant? O Yes, the relationship is significant. O No, the relationship is not significant. (c) Develop a scatter diagram for the data. y 45 y 45 y 45 y 45 T 40 40- 40 40 35 35- 35 35 30 30 30 30 25 25 25 25 20 20 20 20 15 15 15 15 10 10 10 10 5. 5. 5. 5 20 25 30 35 40 45 20 25 30 35 40 45 20 25 30 35 40 45 20 25 30 35 40 45 Does the scatter diagram suggest an estimated regression equation of the form ý = b, + b,x…
(1) Write out the regression equation (2) What is the sample size used in this investigation? (3) Determine the values of *, ** and ***, ****
what does regression analysis mean? What can you tell from it?
Example The marketing manager of Cadbury wants to test the effect of price on sales. Regression model: Sales = β0+ β1Price + error 1) In addition to price, the marketing researcher would like to find out whether there is a systematic trend in the sales. In other words, are sales increasing or decreasing over time? In order to test whether there is a systematic time trend in sales, in addition to the effects of price, please: Tip: the dependent variable is still sales. The independent variables would include price and weeknr (to capture time trend). Write the regression model for question 1 use the examle above to guide you?
What is the null hypothesis to test the significance of the slope in a regression equation? Multiple Choice Ho:B 20 Ho: Bs0 O Ho: B = 0 Ho: B 0
how you will calculate the degrees of freedom in multiple linear regression and in simple linear regression?
What is regression R2 ? Explain both with formula and its meaning in a linear regression model? What does it mean if you have a low regression R2 ?
Discuss the reasons and situations in which researchers would want to use linear regression. How would a researcher know whether linear regression would be the appropriate statistical technique to use? What are some of the benefits of fitting the relationship between two variables to an equation for a straight line?
Canvas -→ X C0| ® E Exhibit 6 Part of an Excel regression output relating salary for programmer (dependent variable) with three independent variables: Test score, Graduate Degree, and Experience is shown below. Coeffic. Std. Err. t Stat P-value Intercept 7.9448 7.3808 1.0764 0.2977 Test Score 1.1476 0.2976 4.8561 0.0850 Grad. 0.1969 0.0899 2.1905 0.0011 Degree Experience -2.2804 1.9866 -1.0479 0.3679 Refer to Exhibit 6. Based on the Excel output, at 95% confidence (alpha = 0.05) which of the independent variables in the output contributes significantly to explain salary? O Experience Grad Degree Intercept Test score
Ordinal data cannot be analyzed using regression analysis. True False