The business question that I am addressing is whether the price (y-intercept) of a sample of used cars (n=50) has a relationship with the independent variables miles (k), mpg, year, and engine type. The best univariate technique to predict the value of (y) is the mean, which is $26, 268. The best technique to measure the y-intercept is how many miles (k) the used car has been driven by the previous owner. This was found by measuring the strongest correlation between price and the independent variables, its absolute value was thirty-eight percent. * The estimated equation is ŷ= 112.24x+32,162

The best way to interpret this equation is for every additional used car sold at $32,162 there is a decrease of 112k in y. 14.8% of the variation of the price can be explained by the equation. This was found by checking the r-squared, which is a powerful tool in Anova; it measures how well future outcomes are likely to be predicted by the model. The reason why we do hypothesis testing is; it’s an assertion about the distribution of one or more random variables. The hypothesis test can be set up:

H0: β1 = 0 With Alpha .05
Ha: Β1 ≠ 0
Reject H0, if p value is <.05
Do not reject Ha, if p value is > or equal to .05
The p value is .006
My decision: Is to reject H0, there is a significant relationship. The predicted model for the dependent variable I got by multiplying the first miles (k) into the equation ŷ= -112.24(100,000) +32,162 which gave me -11,191, 832. This means miles are predicted to decrease by 11,191,832 when price goes up by one. There is a strong negative relationship. The independent variables will affect price of used cars differently. The miles (k) of the car are going to increase/decrease the price of the car, if the miles on the car are too high (ex: over 120,000 miles; price $9,000 also depending on brand of car). The mpg (how many miles car travels on single gallon) is going to increase/decrease sales price of the car if...

...Regression Analysis (Tom’s Used Mustangs)
Irving Campus
GM 533: Applied Managerial Statistics
04/19/2012
Memo
To:
From:
Date: April 19st, 2012
Re: Statistic Analysis on price settings
Various hypothesis tests were compared as well as several multiple regressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35 used Mustangs and 10 different...

...Simple Linear Regression in SPSS
1.
STAT 314
Ten Corvettes between 1 and 6 years old were randomly selected from last year’s sales records in Virginia Beach, Virginia. The following data were obtained, where x denotes age, in years, and y denotes sales price, in hundreds of dollars. x y a. b. c. d. e. f. g. h. i. j. k. l. m. 6 125 6 115 6 130 4 160 2 219 5 150 4 190 5 163 1 260 2 260
Graph the data in a scatterplot to determine if there is a possible linear...

...Regression Analysis: A Complete Example
This section works out an example that includes all the topics we have discussed so far in this chapter.
A complete example of regression analysis.
PhotoDisc, Inc./Getty Images
A random sample of eight drivers insured with a company and having similar auto insurance policies was selected. The following table lists their driving experiences (in years) and monthly auto insurance premiums.
Driving Experience (years) Monthly...

...
MATH533: Applied Managerial Statistics
PROJECT PART C: Regression and Correlation Analysis
Using MINITAB perform the regression and correlation analysis for the data on SALES (Y) and CALLS (X), by answering the following questions:
1. Generate a scatterplot for SALES vs. CALLS, including the graph of the "best fit" line.
Interpret.
After interpreting the scatter plot, it is evident that the slope of the ‘best fit’ line is positive, which...

...Linear-Regression Analysis
Introduction
Whitner Autoplex located in Raytown, Missouri, is one of the AutoUSA dealerships. Whitner Autoplex includes Pontiac, GMC, and Buick franchises as well as a BMW store. Using data found on the AutoUSA website, Team D will use Linear Regression Analysis to determine whether the purchase price of a vehicle purchased from Whitner Autoplex increases as the age of the consumer purchasing the vehicle increases. The data set...

...The simple regression model (SRM) is model for association in the population between an explanatory variable X and response Y. The SRM states that these averages align on a line with intercept β0 and slope β1: µy|x = E(Y|X = x) = β0 + β1x
Deviation from the Mean
The deviation of observed responses around the conditional means µy|x are called errors (ε). The error’s equation: ε = y - µy|x
Errors can be positive or negative, depending on whether data lie above (positive) or...

...STA9708
Regression Analysis: Literacy rates and Poverty rates
As we are aware, poverty rate serve as an indicator for a number of causes in the world. Poverty rates are linked with infant mortality, education, child labor and crime etc. In this project, I will apply the regression analysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study, the poverty rates will be the...