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Regression Analysis

ANOVA and Regression Analysis Project

See attachment for missing data tables. Assume that you are working on a team that has been commissioned by a large school district to collect and analyze data related to a recent curriculum experiment designed to improve student scores on state-wide standardized tests. The schools in this district are predominantly large, u

Hypothesis testing

Statistics Problems 1. Given: The paired sample data of the age and alcohol consumption of men result in a linear correlation coefficient close to 0. Conclusion: Older men tend to consume more alcohol than young men What is the error in the stated conclusion? 2. The eruption height and the time interval after erupt

Regression Analysis: Cost Vs Output

Describe each cost category as fixed or variable based upon the following simple regression results where cost is the dependent variable Y and output is the independent variable X. **See attached spreadsheet for formulas and applicable data** Output Cost1 ($) Cost2 ($) Cost3 ($) 0 17,000 11,000 0 100 10,000 7,000 1,000

Statistics Quiz

1)Go out and find at least 20 observations of ordered-pair data where one variable (X) is independent and (Y) is dependent. Here is my problem: Consider the following table, which contains measurements on two variables for ten people: the number of hours the person spent riding a bicycle in the past week and the number of mont

Regression Analysis: Incarceration Services of AIU data

See attached data file. First run a regression analysis using the Incarceration Services column of all data points in the AIU data set from Unit 1 as the independent variable and the Legal Services satisfaction column of all data points in the AIU data set as the dependent variable. Run a second regression analysis using t

Regression Table

2. Assume that you are a policy analyst. Your staff has collected cross-sectional data on the determinants of average length of stay in various hospitals. A staff member hands you the following table or regression results, assuming that you know how to interpret it. Table. Regression Results for the Impact of Various Factors on

ANOVA and Regression Problem

"You work in the shipping and logistics department for Beast Buy, an American mail order company that specializes in pet food for VERY exotic pets. Beast Buy has four warehouses/distribution centers that provide product to each of four different regions in the US; Atlanta services the southeast, Boston services the northeast, Cl

Correlation Coefficient

I need the full answers to the questions in the attached file. They are similar to exercises from Statistics for Engineers and Scientists, William Navidi. Exercise 1 The following table presents shear strengths (in kN/mm) and weld diameters (in mm) for a sample of spot welds. Diameter Strength 4.2 51 4

Great Plains Roofing: Regression analysis for best predictor of sales

Great Plains Roofing and Siding Company inc, sells roofing and siding products to home repair retailers, such as Lowe's and Home Depot, and commercial contractors. The owner is interested in studying the effects of several variables on the value of the shingles sold($000). The marketing manager is arguing that the company shou

Plan with Adequate Information for Hiring Appropriate Employees

A manufacturing plant that produces widgets wants to locate in a new community. The plant personnel officer advertises the employment opportunity and the next morning has 10,000 people waiting to apply for the 1,000 available jobs. It is important to select the 1,000 people who make the best employees because training takes time

Multiple Regression Equation: Example Problems

See file attached for data charts associated with each question. a) A bicycle company wants to measure the effectiveness of different types of advertising media in the promotion of its new bicycle. Specifically, the company is interested in the effectiveness of radio advertising and newspaper advertising. A sample of 22 cit

Descriptive and Probability Statistics: 15 comprehensive problems

1. (A) Classify the following as an example of nominal, ordinal, interval, or ratio level of measurement, and state why it represents this level: zip codes for the state of Pennsylvania (B) Determine if this data is qualitative or quantitative: Nationality (C) In your own line of work, give one example of a discrete and one ex

Statistics: Regression models; elasticities

See attached data file. G = Total U.S. gasoline consumption, computed as total expenditure divided by price index. Pop = U.S. total population in millions GasP = Price index for gasoline, Income = Per capita disposable income, Pnc = Price index for new cars, Puc = Price index for used cars, Ppt = Price index for public

Research Article: Impact of Teamwork on Missed Nursing Care

See attached article. Please briefly describe: Conclusions of the study? Limitations of the study? Variables (i.e, independent/dependent ) What type of study is this? For example randomized, Non randomized, cross sectional, Descriptive? What are the statistical results that led to the conclusion?

Regression Formula: Harry Potter Example

The students in a modern popular fiction class are complaining that every time Rowling writes another book, it gets longer. Their statistics teacher challenges them to show that their complaints are accurate. Using the Harry Potter data below and a 0.05 level of significance, perform a correlation/regression analysis betw

Strengths and weaknesses of correlational and regression studies

1. Discuss the strengths and weaknesses of correlational and regression studies; discuss concepts such as positive and negative correlations, correlation coefficients, confounding, and causality. 2. You read an interesting study in the paper that says that during any given year, statistics show that ice cream consumption an

Statistical Analysis

See attached data file. 2. Sex discrimination. The dataset salary.dat contains salaries and other characteristics of all faculty members of a small college. The data were collected for presentation in legal proceedings in which discrimination against women in salary was at issue. All faculty members represented in the datas

Financial Analysis with Excel

Please utilize the attach Excel file to respond to the following questions. A . Create an XY (scatter) plot to show the relationship between the returns on AT&T and the S&P 500. Describe, in words, the relationship between the returns of AT&T and the S&P 500. Estimate the slope of a regression equation of this data. Repeat for

Probability Distribution, Correlation & Regression Analysis

The scatter plot below shows the relationship between the day of a particular month a stock was valued and the price of the stock in dollars. The horizontal axis represents the day of the month. Use this graph to answer the questions below. Please see the attachment for the scatter plot. (A) How would you describe the r

Multiple Regression Problems using SAS program: Predict GPA

Variables are: id, a numerical identifier for each student; GPA, the grade point average after three semesters; HSM; HSS; HSE; SATM; SATV; which were all explained in class; and GENDER, coded as 1 for men and 2 for women. 1. Create a new variable called SAT which equals SATM + SATV and run following two regressions:

Statistics: Hypothesis Testing and Simple Linear Regression

See attached files. Lab 2: Hypothesis Testing and Simple Linear Regression Purpose: Students will learn (1) use Excel formulas to build contingency tables for the Chi-Square test of independence; (2) use Excel built-in data analysis procedures to perform one-way ANOVA test; (3) use Excel built-in data analysis procedures

Statistics: 7 problems, Hypothesis Testing and Regression Analysis

Please see attached file. Attached (2): 7 statistic questions (.doc) Formulas and Tables (for reference) --------------------------------------------------------------------------------- HYPOTHESIS TESTING Problem 1 thru 4 (don't forget to state your hypotheses, type of test, alpha level, and your decision statisti

Linear Trend Model-Regression analysis

Rubax, a U.S. manufacturer of athletic shoes, estimates the following linear trend model for shoe sales : Qt = a + bt + c1D1 + c2D2 + c3D3 Where Qt= sales of athletic shoes in the tth quarter T = 1,2, â?¦.,28 [2004(I), 2004(II), â?¦., 2010(IV)] D1 = 1 if t is quarter I (winter); 0 otherwise D2= 1 if it is t quarter II