In this task, you can use all functions of R to help you. In a recently conducted study, it was tested whether there is a connection between job satisfaction and income and seniority in nine randomly selected employees. The value attached to job satisfaction is each employee's own assessment, where 1 describes low satisfaction and 10 high satisfaction. Material: annual income (per thousand dollars) years spent in job satisfaction 47 8 5.6 42 4 6.3 54 12 6.8 48 9 6.7 56 16 7.0 59 14 7.7 53 10 7.0 62 15 8.0 66 22 7.8 The result was the material below a) Fit a two-explainer linear regression model to the data with R's function lm(). What happens to job satisfaction as the number of years increases? For explanatory variables, can the null hypothesis that the corresponding regression coefficient is equal to zero be rejected? b) It is assumed that job satisfaction is only related to years in that job. Estimate the regression parameters using R software. What happens to job satisfaction as the number of years increases? Can we reject the null hypothesis that the regression coefficient is equal to zero? c) What difference do you notice in the answers to (a) and (b)? What could be the reason for this difference? Tip: What is assumed about the explainers?

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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Question

In this task, you can use all functions of R to help you. In a recently conducted study, it was tested whether there is a connection between job satisfaction and income and seniority in nine randomly selected employees. The value attached to job satisfaction is each employee's own assessment, where 1 describes low satisfaction and 10 high satisfaction.

Material:

annual income (per thousand dollars)	years spent in job	satisfaction
47	8	5.6
42	4	6.3
54	12	6.8
48	9	6.7
56	16	7.0
59	14	7.7
53	10	7.0
62	15	8.0
66	22	7.8

The result was the material below

a) Fit a two-explainer linear regression model to the data with R's function lm(). What happens to job satisfaction as the number of years increases? For explanatory variables, can the null hypothesis that the corresponding regression coefficient is equal to zero be rejected?

b) It is assumed that job satisfaction is only related to years in that job. Estimate the regression parameters using R software. What happens to job satisfaction as the number of years increases? Can we reject the null hypothesis that the regression coefficient is equal to zero?

c) What difference do you notice in the answers to (a) and (b)? What could be the reason for this difference? Tip: What is assumed about the explainers?

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