economic math

A) Find the linear regression equation (line of best fit), determine the correlation, and then make a prediction.

1. The table below gives the amount of time students in a class studied for a test and their test scores.

Graph the data on a scatter plot, find the line of best fit, and write the equation for the line you draw.

Hours Studied	1	0	3	1.5	2.75	1	0.5	2
Test Score	78	75	90	89	97	85	81	80

Linear Regression Equation: ____________________

Correlation Coefficient (r): _________

Type of Correlation: ______________________

Is the correlation strong? Explain

Using the linear regression equation predict

a students test score if they studied for 4 hours.

2. The table below gives the amount of Krabby Patties made by Spongebob for each year he’s worked.

Graph the data on a scatter plot, find the line of best fit, and write the equation for the line you draw.

Years worked	1	2	3	4	5	6
Patties made	6,500	7,805	10,835	11,230	15,870	16,387

Linear Regression Equation: ____________________

Correlation Coefficient (r): _________

Type of Correlation: ______________________

Is the correlation strong? Explain

Using the linear regression equation predict

how many Krabby Patties he will make after

working 10 years.

3. The table below gives the estimated world population (in billions) for various years.

Year	1980	1990	1997	2000	2005	2011
Population	4400	5100	5852	6080	6450	7000

Linear Regression Equation: ____________________

Correlation Coefficient (r): _________

Type of Correlation: ______________________

Is the correlation strong? Explain

Using the linear regression equation predict

the world population in the year 2015.

4. The table below shows the income for an employee over his first 8 years of work. Use this to estimate

his income for his 15th year of work.

Years	1	2	3	4	5	6	7	8
Income	45,000	46,814	48,212	52,870	54,125	58,532	61,075	62,785

Linear Regression Equation: ____________________

Correlation Coefficient (r): _________

Type of Correlation: ______________________

Is the correlation strong? Explain

Using the linear regression equation predict

his income for his 15th year of work.

B) Attached you will find an excel sheet data on the effect of 5 variables (Cylinder, displacement, horsepower, weight, seconds or acceleration) on the Gasoline consumption per1000miles. Based on the data please workout the following.

a) Regression model

b) Regression coefficient

c) Correlation coefficient between

· Gasoline consumption and cylinder

· Cylinder and displacement

· Gasoline consumption and acceleration

d) Find the p-value for

i. Total regression line

ii. Cylinder

iii. Displacement

iv. Horse power

v. Weight

vi. acceleration

e) identify the variable which has

i. a significant impact

ii. Less significant impact

f) Predict the Gasoline consumption per1000mile using the following data

i. Cylinder --- 6

ii. Displacement –- 2.2

iii. Horse power ---- 2.4

iv. Weight ---- 3.8

v. Acceleration - 12