Consider the average family income and annual savings of nine familiesshown below. Test the significance of your computed correlationcoefficient at a=0.05. *Annual Income (in P10,000) (X)4144475053565961645659Annual Savings (in P10,000) (Y)3.47.78.9.109.87.

Solution-: We find the correlation coefficient =? Test the significance level of computed…

Answered: Consider the average family income and…

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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Listed below are amounts (in millions of dollars) collected from parking meters by a security service company and other companies during similar time periods. Do the limited data listed here show evidence stealing by the security service company's employees? Security Service Company: Other Companies: Find the coefficient of variation for each of the two samples, then compare the variation. 1.3 1.8 The coefficient of variation for the amount collected by the security service company is %. (Round to one decimal place as needed:) OA. Yes. There is a significant difference in the variation. OB. No. There is a significant difference in the variation. O C. Yes. There is not a significant difference in the variation. OD. No. There is a not significant difference in the variation. 1.8 1.9 1.6 1.7 1.7 1.7 1.6 1.8 The coefficient of variation for the amount collected by the other companies is %. (Round to one decimal place as needed.) Do the limited data listed here show evidence of stealing by…
What is your best estimate of the correlation coefficient shown here? VARIASLE X +1.0 +0.8 0.0 -0.8 -1.0
We have measurements from eight companies for the % workforce change in 2010 from 2009 and the % change in profits from 2010 to 2011. % workforce change (x): 1.0 % profit change (y): 1.5 -0.4 -2.6 -3.8 -5.8 -2.5 -0.1 0.4 0.4 0.1 -0.2 -0.5 -7.5 0.2 0.3 We can calculate: Er = -12.7, Ex² = 64.51, Συ--6.8 , Σ 57, Σεy- 46.35. Find the sample correlation between the two variables, and fit a simple linear model to the dataset. Also, plot the residuals, ri, against xi, and comment on the fit of the model.
Past data on household income and expenditure reveal that: (a) The average absolute increase in income in relation to increase in expenditure is $ 1.5 crore and (b) the average absolute increase in expenditure in relation to increase in income is $ 0.50 crore. Find the co-efficient of correlation between household income and expenditure.
1. The chart of data represents the heart rate (beats per mimute) of a jogger over time (minutes). Time (Min) 1 3 4 6. 7. 8. BPM 81 84 86 91 97 102 108 112 la. Write the cquation of the Line of Best Fit Your answer 1b. What is the correlation coefficient? Your answer
How much would you expect systolic blood pressure to change if a person commits to reducing their cigarette consumption by 1 cigarette per day?
Which of the following correlation (r) show a negative association between 2 variables? 0.2 -1.4 0.4 -0.8
5If the linear correlation coefficient between the weights (in kg) and heights (in inches) of 6 randomly selected males is 0.95, then 95% of the variation in weights of males can be explained by the linear correlation between height and weight? 1. True 2. False
The following are the monthly figures of advertising expenditure and sales of a firm. It is generally found that advertising expenditure has its impact on sales after 2 months. Allowing for this time lag, calculate coefficient of correlation. Advertising Expenditure ('000) Sales Months Advertising Expenditure ('000) Months Sales 1,200 July Aug. Jan. 50 140 2,400 Feb. 60 1,500 160 2,600 March 70 1,600 Sep. 170 2,800 90 2,000 Oct. 190 2,900 April May 120 2,200 Nov. 200 3,100 June 150 2,500 Dec. 250 3,900
y: 30 -10 50 10 1 25 -15-60 15 8 35 20-5 7. 10 9. -40 -5 X: 9. 3 4 6. 0.05. Test for significant positive (linear) correlation at a =
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Consider the average family income and annual savings of nine families shown below. Test the significance of your computed correlation coefficient at a=0.05. * Annual Income (in P10,000) (X) 41 44 47 50 53 56 59 61 64 56 59 Annual Savings (in P10,000) () 3. 4 7. 8. 6. 10 8. 9, 4)