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# Regression Analysis

### Regression Analysis Interpretations of population and sales data. Interpret the findings and discuss implications for business.

A bank has offices in six different markets. It is feasible to say the annual sales of offices are related to the population of the communities they are in. The dependent variable, y, is annual sales. The independent variable, x is market population. A regression analysis was conducted using Excel and the results of this

### Regression analysis in Minitab Statistics

Regression Analysis We want to investigate the relationship of several factors to employees' current salaries. Included in the data is a sample of 37 employees. The first column is an ID. The second column is the time, in months, in their current job (VAR 1). The third column is the time, in years of related job experienc

### Interpreting the stepwise regression output

Please see the attached file. 13.30 A researcher used stepwise regression to create regression models to predict birth rate (births per 1000) using five predictors, life exp (life expectancy in yeras), inform (infant mortality rate), density (population density per square kilometer), GDP cap (Gross domestic product per capita),

### Correlation analysis ...

1. (a) How does correlation analysis differ from regression analysis? (b) What does a correlation coefficient reveal? (c) State the quick rule for a significant correlation and explain its limitations. (d) What sums are needed to calculate a correlation coefficient? (e) What are the two ways of testing a correlation coefficient

### Determining Regression Equation: Real Estate Example

Write out the regression equation (Refer to the Real Estate data) which reports information on homes sold in the Denver, and use the selling price of the home as the dependent variable and determine the regression equation with size of the house, and the distance from the center of the city.

### Hypothesis Testing for the slope of a least squares regression line.

An advertising firm wishes to demonstrate to potential clients the effectiveness of the advertising campaigns it has conducted. The firm is presenting data from recent campaigns, with the data indicating an increase in sales for an increase in the amount of money spent on advertising. In particular, the least-squares regression

### Regression analysis - Least Squares Regression Line

What is the least squares regression line equation ? What are the slope and the y-intercept? What is the R-squared value? Conclusion make specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

### Forecasting: prediction based on Regression equation

A regional power company has generated the following regression model for forecasting the total amount of electrical power used by its customers(In megawatt hours) each quarter. Yt=162.6+3.25t-16.26Q1-32.52Q2 +65.04Q3 Qi=1 if the data is associated with quarter i Qi=0 otherwise See attached file for the problem.

### Quantitative Research Methods

Please see the attached file. 1) Help Elaborate Purpose Statement 100-200 words The dependent variable (Cost of the home in \$) is determined by independent variables (Square footage, Number of bedrooms and Age) The most important independent variable in this relationship is the Square footage because the Cost of the hom

### Interpreting Regression Coefficients

A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y = sales price (in thousands of dollars) x1 = total floor area (in square feet) x2 = number of bedrooms x3 = distance to nea

### Correlation, Causation and Regression

Question 1: What is correlation? Does correlation prove causation? Why or why not? Explain and provide examples to support your explanation. Questions 2: What are the differences between regression and correlation analysis?

### Home Insulation Manufaturer: Regression Coefficients

Cellulon, a manufacturer of a home insulation, wants to develop guidelines for builders and consumers regarding the effects (1) of the thickness of the insulation in the attic of a home and (2) of the outdoor temperature on natural gas consumption. In the laboratory they varied the insulation thickness and temperature. A few of

### Regression Coefficient Tests and Confidence Intervals

Please answer the following questions: (a) Explain why a confidence interval for the slope or intercept would be equivalent to a two-tailed hypothesis test. (b) Why is it especially important to test for a zero slope?

### Basic estimation techniques

Given cellar capacity constraints, The Kalamazoo Brewing Company (KBC) currently sells its microbrews in a seven-state area. The company's marketing department has collected data from its distributors at each state. Data on the quantity and price (per case) of microbrews sold in the state of Ohio, as well as the average incom

### Multiple regression

See attachment. 7. The following equation was estimated as the demand function for gasoline (number of observations equals 1,682, and standard errors are in parentheses): _lnQ = 3.95 - 0.525lnP - 0.263lnAge + 0.129lnY - 0.211lnPc + 0.796LnD - 0.103U + 0.182R_ (1.51) (0.105) (0.920)

### Statistics - Quantitative Decision

The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the last 6 months. Develop a regression model to predict selling price based on the square footage, number of bedrooms, and age. Use this to predict the selling price of a 10 year old, 2000 square

### Correlation and Regression - Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. ...

Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. X: 37, 47, 57, 67, 77, 87 Y: 5, 8, 10 ,

### Statistics - Regression Hypothesis..

Dependent Variable (Y axis): The variable that is being predicted or estimated is the account balance Independent Variable (X axis): A variable that provides the basis for estimation is the number of ATM transactions per month. It is the predictor variable. Now I need to perform a regression hypothesis test on the data.

### Time series analysis& Hypothesis testing

Homework Assignment Question #1: The Prescott Electric Windings Company, which produces medium-scale electric motors for the fishing industry, is concerned about their number of orders over the past several years. Marty Sturgeon, general manager said, "With this decrease in orders I'm worried that I'm going to have to lay

### Energy Consumption and Temperature

Energy Consumption and Temperature In Data Set 9, use the 10 average daily temperatures and use the corresponding 10 amounts of energy consumption (kWh). (Use the temperatures for the horizontal scale.) Based on the result, is there a relationship between the average daily temperatures and the amounts of energy consumed? Try

### Linear Regression Equation

Given the following data: Height 71 70.5 71 72 70 70 66.5 70 71 (in) Weight 125 119 128 128 119 127 105 123 115 (lbs) Find the linear regression equation.

### Confidence Limit - In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald's employees. (a) Write the fitted regression equation. (b) State the degrees of freedom for a twotailed ... [See the attached questions file.]

In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald's employees. (a) Write the fitted regression equation. (b) State the degrees of freedom for a twotailed test for zero slope, and use Appendix D to find the critical value at &#945; = .05. (c) What is your conclusion about the slope? (d) Int

### Regression: Performing Regression Analysis

Perform Regression analysis (1) A (\$3.76, \$3.80)? B (\$3.87, \$3.89)? C (\$3.85, \$3.84)? (2) A (\$3.87, \$3.89)? B (\$3.91, \$3.93)? C (\$3.95, \$4.29)? (3) A (\$3.98, \$3.99)? B (\$4.03, \$4.05)? C (\$3.99, \$4.05)? [Please the attached questions file].

### Production management, moving averages forecasting method, exponential smoothing method, Regression, Evaluating Cost

1. Keith has developed a simple linear analysis utilizing the number of tourists an as independent variable (predictor). Keith is predicting the sales volume for his retail store. The results of the regression analysis generated a correlation coefficient of (.85) and constants a=23000 and b=4. Three years from now the number of

### Scatter Plot and Trend Line

Please see the attached file. Please answer these questions based on the data file Packages. a. Develop a scatter plot of the data with the dependent variable, cost, on the vertical axis and the independent variable, weight, on the horizontal axis. Does there appear to be a relationship between the two variables? Is the re

### Regression line - Given the following ordered pairs (x, y): (5,-2) (3,0) (2,1) (1,2) (0,3) (2,1), compute the equation of the regression line. Just type in the right side of the equation, and use 1 decimal place of accuracy for any numeric values.

Given the following ordered pairs (x, y): (5,-2) (3,0) (2,1) (1,2) (0,3) (2,1), compute the equation of the regression line. Just type in the right side of the equation, and use 1 decimal place of accuracy for any numeric values.

### Regression Analysis: Predict Assessed Value Based

1. Suppose we want to develop a model that can be used to predict assessed value based on heating area. Based on the following sample of 15 homes; a. Find the regression coefficients a and b b. Interpret the meaning of the Y intercept a and slope b. c. Use the regression model to predict the assessed value of

### Predicting Number of Touchdowns

Q2 Can you predict the number of touchdowns from the following variables: attempts, yards, and yards per game? a Develop a correlation matrix for the 3 predictor variables, do you suspect multicolinarity? b What is your multiple regression equation, is it significant? c Predict the number of touchdowns for a ba

### The Effect of Sack Yardage has on Quarterback Ratings

Analyze the effect of sack yardage has on quarterback rating. a. Does the sack yardage predict the QB rating? b.What is the regression equation and is this a significant equation? c. What is your prediction for the QB rating of a quarterback that has 300 sack yards? Quarterback Passing Player sack yardage

### Statistics - Regression..

1. A company reports that the results of a phone survey indicate 80% of Americans prefer their product, with only a 3% margin of error. 2. A fourth-grade teacher takes the math scores of the 10 tallest and 10 shortest students in the class, and ... [Please see the attached question file.]