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Regression Analysis

Multipe Regression Equation for Size and Selling Price

A real estate association in a suburban community would like to study the relationship between the size of a single-family house (as measured by number of rooms) and the selling price of the house (in thousands of dollars). Two different neighborhoods are included in the study, one on the east side of the community (=0) and the

Regression Analysis

Can demographic information be helpful in predicting sales at sporting goods stores? The data at left are monthly sales totals from a random sample of 38 stores in a large chain of nationwide sporting goods stores. All stores in the franchise, and thus within the sample, are approximately the same size and carry the same merc

Hypothesis Identification Article Analysis: What can analytics do for a company?

Using the "Competing on Analytics" article by Thomas H. Davenport prepare an analysis of how to compete on analytics. Have at least one industry example from the article. State at least one principle from the article. Based upon the article briefly conclude your review with explaining 'What can analytics such as statistics do

Multiple regression analysis: leadership change

Give an example of how you may use multiple regression to answer a question related to the impact of leadership change on employee attitudes scores, teambuilding training and performance outcomes. State a null and alternate hypothesis and clearly define your variables (independent and dependent variable).

Please help with these statistic problems

Problem 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

Ratio-to moving-average method as a forecasting method

See attached data file. 58. The number of employees on the payroll at a food processing plant is recorded at the start of each month. These data are provided in the file P13_03.xlsx. a. Is there a seasonal pattern in these data? If so, how do you explain this seasonal pattern? Also, if necessary, deseasonalize these data

MCQs: Hypothesis Testing & Time series Analysis

See attached file for graphs. 1) if the null hypothesis is not rejected, it can be assumed the proportions are __________ and the differences in them are due to chance. a) equal b) unequal c) small d) large 2) A pharmaceutical company is testing the effectiveness of a new drug for lowering cholesterol. As part of this

Regression Models that Predict Selling Price & SAT Scores

Thirteen students entered the undergraduate business program at Rollins College two years ago. The following table indicates what their grade-point averages (GPAs) were after being in the program for two years and what each student scored on one part of the SAT exam when he or she was in high school. Is there a meaningful relati

Linear regression to justify advertising

You are the marketing manager, in charge of a $1 million advertising budget, for two branches of the Long and Foster Real Estate Company. Because of slumping sales, the company president announces plans for an across-the-board budget cut of 10 percent. However, each department manager will have an opportunity to present his/he

Regression Analysis: Analyzing Job Satisfaction

Prepare a report using Excel as your processing tool to process 3 simple regression analyses. Create a graph with the trend-line displayed for each of the 3 different regressions. 1. 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

Statistics: Track and Field

The long jump is a track-and-field event in which a competitor attempts to jump a maximum distance into a sandpit after a running start. At the edge of the pit is a takeoff board. Jumpers usually try to plant their toes at the front edge of this board to maximize their jumping distance. The absolute distance between the front ed

Statistics: Cross sectional data, time series data; priori hypothesis

See attached file. Using Data set "G," choose the dependent variable (the response variable to be "explained") and the independent variable (the predictor or explanatory variable) as you judge appropriate. Use a spreadsheet or a statistical package (e.g., MegaStat or MINITAB) to obtain the bivariate regression and required gr

Data tables with excel regression with dependent variable

The data table in the excel file tabulates a pizza parlor's advertising expenditures and sales for 8 consecutive quarters. The marketing manager wants to know how much of an impact current advertising will have on sales two quarters from now. While running a regression with the dependent variable sales and the independent var

Regression Analysis

The regression analysis in the Excel file relates US annual energy consumption in trillions of BTUs to the independent variable US Gross Domestic Product' (GDP) in trillions of dollars. How much of the variation in energy consumption can be explained by variation in the gross domestic product? which one? A-About 99.

Regression Analysis: Predicted value

The regression analysis in the Excel file relates US annual energy consumption in trillions of BTUs to the independent variable US Gross Domestic Product (GDP) in trillions of dollars. Excel Output US Energy Consumption (in trillion BTUs) vs. Gross Domestic Product ($trillions) Regression Statistics

Simple regression or multiple regression

Market researcher Ally Nathan is studying the relationships among price, type (classical or steel string), and consumer demand for acoustic guitars. She wants to find the relationship between demand and price, controlling for type. To determine this relationship, she should A-Run a simple regression of the dependent variable


In a regression analysis with multiple independent variables, multicollinearity can be caused by: A- A strong nonlinear relationship between the dependent variable and one or more independent variables. B-A strong heteroskedastic relationship between the dependent variable and one or more independent variable.

Research: Regression and Correlation Analysis

Please help answer the following question. Provide at least 200 words. What is the possible uses of regression and correlation analysis in doctoral-level research? Would I be able to use these techniques in my dissertation, or any application in other areas?

Regression Analysis: Residual & Slope

The age, in years, of 11 children and the number of words in their vocabulary are Age Vocab 1 3 2 440 3 1200 4 1500 5 2100 6 2600 3 1100 5 2000 4 1525 6 2500 1) Compute the re

Description of Correlation and Regression Analysis

6. For the following scores, X Y 3 12 6 7 3 9 5 7 3 10 a. Compute the Pearson correlation. b. With a small sample, a single point can have a large effect on the magnitude of the correlation. Change the score X = 5 to X= 0 and compute the Pearson correlation again. You should find that the change ha

Regression Analysis and Correlation Coefficient..

See data file attached. Do workers who receive more education miss fewer work days? The attached data represents the number of sick days taken by 20 Delta workers along with the number of hours of education they received. Analyze the data using both regression and correlation techniques. Use Excel to show output / results.

Critical Value for Sales and Advertising Data

Exhibit 12-2 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained. Y with hat= 12 + 1.8x n= 17 SSR = 225 SSE = 75 sb1= 0.2683 1. Refer to Exhibit 12-2. The critical F