### Statistical Analysis and Linear Regression#### 3. Analyze the Relationship Between Experience and SalaryUse the following table to perform the tasks described below, considering unit price (in dollars) as your independent variable $x$ and units sold (in thousands) as your dependent variable $y$:| Years of Experience | Salary in $1000s ||--------------------:|------------------:|| 2 | 15 || 3 | 28 || 5 | 42 || 13 | 64 || 8 | 50 || 16 | 90 || 11 | 58 || 1 | 8 || 9 | 54 |a. **Find the Linear Correlation Coefficient** Calculate the linear correlation coefficient to determine the strength and direction of the linear relationship between years of experience and salary.b. **Find the Line of Best Fit** Determine the equation for the line of best fit (linear regression line) for the given data set. This line minimizes the sum of the squared vertical distances between the observed values and the line itself.c. **Predict Salary for a Given Unit Price** Using the line of best fit, predict the salary (in thousands of dollars) for a specific years of experience if the unit price were 0.85.#### Explanation of Tasks:**a. Linear Correlation Coefficient:**- This statistical measure will tell us how strongly the years of experience (independent variable) is related to the salary (dependent variable). **b. Line of Best Fit:**- The line of best fit provides us with a model to predict salary based on years of experience. The equation of the line will be in the form $ y = mx + b $, where $ m $ is the slope and $ b $ is the y-intercept.**c. Prediction:**- Once the equation of the line of best fit is known, plug in the given unit price (0.85) to predict the corresponding salary.Feel free to use software tools like Excel, Google Sheets, or statistical software to perform these calculations, which often involve multilinear regression functions.

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Description: ### Statistical Analysis and Linear Regression#### 3. Analyze the Relationship Between Experience and SalaryUse the following table to perform the tasks described below, considering unit price (in dollars) as your independent variable $x$ and unit

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Statistics

Use the table to find the following, unit price being your (x) and units sold (y). a. Find linear correlation coefficient. Years of Experience Salary in 1000$ 2 3. 15 28 42 13 64 50 16 90 11 58 8 54 b. Find the line of best fit. c. How many units will sell if the unit price was 0.85.

Use the table to find the following, unit price being your (x) and units sold (y). a. Find linear correlation coefficient. Years of Experience Salary in 1000$ 2 3. 15 28 42 13 64 50 16 90 11 58 8 54 b. Find the line of best fit. c. How many units will sell if the unit price was 0.85.

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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