find linear correlation coefficient, P value, and test statistic. ### Linear Correlation Between Court Income and Justice Salaries#### Dataset OverviewListed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars.| Court Income | 64.0 | 404.0 | 1567.0 | 1131.0 | 270.0 | 250.0 | 111.0 | 1555.0 | 30.0 ||--------------|-------|-------|--------|--------|-------|-------|-------|--------|-------|| Justice Salary | 30 | 43 | 91 | 58 | 44 | 62 | 26 | 27 | 18 |#### Instructions1. **Construct a Scatterplot** - Plot the *Court Income* values on the x-axis. - Plot the *Justice Salary* values on the y-axis. - Each point on the scatterplot corresponds to a pair of court income and justice salary values.2. **Calculate the Linear Correlation Coefficient (r)** - Use the formula: \[ r = \frac{n(\sum xy) - (\sum x)(\sum y)}{\sqrt{[n\sum x^2 - (\sum x)^2][n\sum y^2 - (\sum y)^2]}} \] where - \( n \) is the number of pairs, - \( x \) represents *Court Income*, - \( y \) represents *Justice Salary*.3. **Find the P-value** - Use an α level of 0.05. - The P-value helps determine if the linear correlation is statistically significant.4. **Analysis** - Based on the results, determine if there is sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries. - Discuss whether it appears that justices might profit by levying larger fines.#### Result Interpretation- **Scatterplot**: Visual representation of the data to look for any pattern or trend.- **Linear Correlation Coefficient (r)**: Indicates the strength and direction of the linear relationship. - Values close to 1 imply a strong positive correlation. - Values close to -1 imply a strong negative correlation. - Values around 0 imply no correlation.- **P-value**: - A P-value less than

The linear correlation coefficient uisnsg Excel is obtained as follows: In Excel sheet, enter…

Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a=0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 64.0 404.0 1567.01131.0 270.0 250.0 111.0 155.0 30.0 P Justice Salary 30 43 91 58 44 62 26 27 18 Court Income Court Income Court Income Court Income The linear correlation coefficient r is

Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a=0.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 64.0 404.0 1567.01131.0 270.0 250.0 111.0 155.0 30.0 P Justice Salary 30 43 91 58 44 62 26 27 18 Court Income Court Income Court Income Court Income The linear correlation coefficient r is

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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Average Income 19320 17554 17310 15589 15266 15078 12749 9351 8866 4952 3627 3412 2554 2296 1871 1809 1710 1621 1345 1282 1171 1109 1091 810 585 Average Life Expectancy 76.25 75.3 78.65 75.51 76.19 76.36 73.73 73.9 76.38 71.16 64.19 74.35 57.53 56.64 62.71 57.34 54.98 46.93 52.24 53.44 60.99 57.21 49.99 45.91 60.03 In this practice assignment, you will use spreadsheet regression or the online regression calculator at http://www.alcula.com/calculators/statistics/linear- regression to examine the relationship between average annual income and average life expectancy in a country. This relationship is called the Preston curve. Open QR 8D Spreadsheet_Practice, which gives the average annual income and average life expectancy in 25 low-income countries. Each row corresponds to a country. Use technology (spreadsheet regression or the Alcula website given above) to create a scatterplot and regression equation for the Preston curve data. Round all answer values to the nearest ten thousandth…
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