Explore BrainMass

# Regression Analysis

### Intrinsic, Extrinsic and Overall Job Satisfaction Report in Excel

Prepare a report using Excel as your processing tool to process three simple regression analyses. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent varia

### Use of ANOVA, One-Way, Two-Way, R-Square in Regression

Short Answer - One paragraph per response; your own words! Reference links may be included. Question 1: The F test is used in Analysis of Variance (ANOVA). When would a researcher use an ANOVA? Explain. Questions 2: A research assistant is contemplating whether to use a One Way ANOVA or a Two Way ANOVA. The research as

### Finding the Best Equation to Predict Y: MegaStat

See attached Excel spreadsheet. "Y" is the dependent variable and the "X"'s are independent variables. Use MegaStat and its Regression capabilities to find the "best" equation that predicts Y based upon the X's. (Don't accept the first equation you find, try others also.) What do you notice in the regression analysis? Which v

### Statistics: F test used in ANOVA, R-square role in regression analysis

The F test is used in Analysis of Variance (ANOVA). When would a researcher use an ANOVA? Explain. A research assistant is contemplating whether to use a One Way ANOVA or a Two Way ANOVA. The research assistant comes to you for consultation. Explain to this research assistant the differences between these two ANOVA tests.

### Regression Analysis of Cafe Average Hourly Sales

See attached data file. Perform a regression analysis on your data using Microsoft® Excel®. It will be sufficient if you have one dependent and one independent variable and collect your data sets for those. You are welcome to do a multi variable regression analysis if you like to . Be sure to attach the results of the

### ANOVA, R-square, Significance of Regression Model: Example

Two experts provided subjective lists of Nine school districts that they think are among the best in the country. For each school district, the average class size, the combined SAT score and the percentage of students who arrived at a four-year college were provided. The following ANOVA table contains information that was ge

### Realtor using regression analysis for house prices

You are a realtor with a small business. You use a simple 2 variable linear regression analysis for quick first glance house price estimates using square footage of the house. You are asked by a customer what the price for his house would be given that his house has 1,500 square feet. The number you are trying to explain is the

### Regression Hypothesis Test on Real Estate Data

Test the Hypothesis that homes located closer to the centre of the city, are higher in price than those homes located further away from the centre of the city. -Perform a regression hypothesis test on the data -Include a graph showing the results -Include the results of your computations, using graphical and/or tabular met

### Regression Analysis: Hypothesis Testing Example Problem

A research would like to examine the effects of humidity on eating behavior. It is known that laboratory rats normally eat an average of µ = 21 grams of food each day. The research selects a random sample of n = 16 rats and places them in a controlled atmosphere room in which the relative humidity is maintained at 90%. The dail

### Regression Model for predicting risk for stroke.

A 10 year study by the American Heart Association provided data on how age, blood pressure and smoking relate to the risk of strokes. Data from a portion of this study are shown below. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10 year period. For the smoker variable, 1 indi

### General Statistics

5 Answer questions 5-8 using the following information: Test the hypothesis that the treatment means for samples given below are equal. Use the .01 significance level. Treatment 1 Treatment 2 Treatment 3 22 34 13 20 31 10 21 25 14 18 25 11 19 32 30 The decision rule is: Choose one answer. a. Reject the nul

### Statistics: Multi Regression analysis

We want to determine the primary factors that affect Motor Vehicle Theft crime rates in the United States. The statistical analysis of the data involves multiple-regression analysis. This problem is for Graduate/Masters level 1.What are the primary determinants of Motor Vehicle Theft crimes in the United States? 2. What

### Artsy Company: Difference in pay rates by job grade, time in grade and by sex

Artsy Case The Artsy Corporation has been sued in the United States Federal Court on charges of employment discrimination under Title VII of the Civil Rights Act of 1964. (Artsy is an actual corporation and the data given in the case is real, but the name has been changed to protect the firm's true identity.) The litigation at

### SPSS Input

A Survey of 50 Companies In January '08, fifty customers of a lumber manufacturer were surveyed regarding their satisfaction with products and service. These customers buy from the supplier and sell to retail chains like Home Depot and Lowes. Shortly after, the manufacturing company was sold. In June '08, the customers were

### STATISTICS

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?

### Statistics: Explain why most researchers use default(Enter) method for model building.

Explain why most researcher use the default(Enter) method for model building.

### Multiple Regression & Seasonal Forecasting

This solution describes how to do multiple regression using Excel and the Megastat plugin. Students are given step-by-step instructions on how to use the MegaStat plugin for Excel and told why Excel's Data Analysis Toolpak isn't reliable for rigorous statistical analysis. Attachments include example spreadsheets, a video tutoria

### Statistics: Correlation analysis, McDonald employees, birthrates, aviation shipments

See attached file for 6 problems 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

### Multiple Regression Analysis and Hypothesis Test

The Excel file contains this data on weekly gross revenues, television advertising expenditures, and newspaper advertising expenditures for Showtime Movie Theaters, all measured in thousands of dollars. Weekly Gross Revenue Television Advertising Newspaper Advertising 96

### Elasticity Case and Questions: National consumption of chicken

There are 3 attached files. One is the case with actual deliverables highlighted in yellow. One is the spreadsheet with necessary data. The last is a document with examples of how the tables are to be done. The numbers on the table example sheet are not right, they are just there to show how the outcome should look.

### Statistics: Finding Predicted Value and Prediction Interval

Refer to the data below: CO2 314 317 320 326 331 339 346 354 361 369 Temperature 13.9 14.0 13.9 14.1 14.0 14.3 14.1 14.5 14.5 14.4 a) Find the predicted temperature (in degrees C) when the CO2 concentration is 370.9 parts per million b) Find a 99% prediction interval estimate of the temperature (in degrees C) w

### Statistics: Regression equation, predicted Y value, Pearson correlation

22. For the following data: X y 1 2 4 7 3 5 2 1 5 14 3 7 a. Find the regression equation predicting Y from X. b. Use the regression equation to find a predicted Y from each X. c. Find the difference between actual Y value and the predicted Y value for each ind

### Relationship Between Volume and Cost Productions

VOLUME CHEMICAL (This problem was intended to be solved using the computer.) You are involved in an analysis of the relationship between the cost and the volume of production. You have collected the following inflation-adjusted data. PRODUCTION UNITS COSTS 700 \$61,750 1,450 64,450 1,500 66,000 1,750 69,438 2,

### Regression analysis: TV sales

Market area TV sales Income\$ Number of competitors 1 3200 42000 5 2 3350 46000 3 3 2800 35000 6 4 4000 51000 4 5 3600 47000 4 6 3500 48000 3 7

### Regression equation, predictions

Identify the regression equation and make the prediction. Show your procedure, or explain how you reached your answer. Costs of Television: Find the best predicted quality score of a Hitachi television with a price of \$1900. Is the predicted quality score close to the actual quality score of 56? Price 2300 1800 2500 2700 2

### Scatterplot, Regression Analysis and Correlation Hypothesis Test

Construct a Scatterplot of the raw data. Then, run the Correlation/Regression program. Costs of Television: Listed below are prices (in dollars) and quality rating scores of rear-projection televisions. All of the televisions have screen sizes of 55 or 56 inches. Is there sufficient evidence to conclude that there is a line

### Regression

Identify the regression equation and make the prediction. Show your procedure, or explain how you reached your answer. Commuters and Parking Spaces: The Metro-North Station of Greenwich, CT has 2804 commuters. Find the best predicted number of parking spots at that station. Is the predicted value close to the actual value of

### Correlation and Regression Prediction

Identify the regression equation and make the prediction. Show your procedure, or explain how you reached your answer. Find the best predicted cost of subway fare when the CPI is 182.5 (in the year 2000) CPI 30.2 48.3 112.3 162.2 191.9 197.8 Subway 0.15 0.35 1 1.35 1.5 2 Fare Regression equation: Predicted value:

### Regression Equation: Calculation of Prediction Interval

Find the prediction interval. Construct the indicated prediction interval for an individual y. The equation of the regression line for the paired data below is: y-hat = 6.1829 + 4.3394x and the standard error of estimate is se = 1.6419. Find the 99% prediction interval of y for x = 11. The summation values are l

### General Statistics

Directions: You may include the statistical software output, but you must also include a well-written explanation of the findings. Be sure to answer the question asked in each problem, and explain why, with reference to your output. If you calculate the answers manually, be sure to show your work. I would prefer a Word document