Problem: The demand for airplane passengers (Y) is a function of a average fare (X1), the fare of the competing airline, and the annual per capital income of the passengers(X3) Passenger seat sold Fare of the Fare of the competing Annual Per Capital of the airline airline a
1. If the daily stock price, x, of United Technology is normally distributed with mean 6.56 and standard deviation 2.4, calculate the probability that in a randomly selected ay the price will be between $3.25 and $7.36. Hint: Review normal distribution. 2. An industry is comparing its performance against an industry benchmar
Perform a regression analysis on the data using Microsoft Excel.
1. The following sample observations were randomly selected. X: 4, 5, 3, 6, 10 Y: 4, 6, 5, 7, 7 a. Determine the regression equation. b. Determine the value of Y' when X is 7. c. Determine the standard error of estimate. d. Suppose a large sample is selected (instead of just 5). About 68% of the prediction
The manager of a seafood restaurant was asked to establish a pricing policy on lobster dinners. Experimenting with prices produced the following data: Average Number Sold per Day, y Price, x 200 $6.00 190
Use Megastat (and show all steps) to solve the following problem: a) Plot the data on U.S. general aviation shipments (see attachment for data). b) Describe the pattern and discuss possible causes. c) Would a fitted trend be helpful?
Use the data in the table, which shows the personal income and outlays (both in trillions of dollars) for Americans for 11 recent years. (Source: U.S. Commerce Department, Bureau of Economic Analysis) Personal income, x Personal outlays, y 5.6 4.6 5.8 4.9 6.2 5.2 6.5 5.5 6.9 5.8 7.4 6.1 7.8
The following data gives the starting salary for students who recently graduated from a local university and accepted jobs soon after graduation. The starting salary, grade jobs soon after graduation. The starting salary, grade- point average (GPA), and major (business or other) are provided. Salary $29,500 $46,000 $39,800 $36,
Calculate the regression equation using Excel, including the R Square, Slope, Intercept and the formula Y = a +bX with % Welfare as the X variable and % Passing as the Y variable.
In the following regression, x = weekly pay, y = income tax withheld and n = 35 McDonalds employees. a) write the fitted regression equation b) state the degrees of freedom for a two tailed test for zero slope and use Appendix D to find the critical value at alpha = .05 c) what is your conclusion about the slope? d) interp
I. Simple Regression to Estimate Parameters. (A) Simple regression model with sales revenue as the dependent Y-variable and R&D expenditures independent X-variable. (B) Simple regression model with profits as the dependent Y-variable and R&D expenditures independent X-variable.
An expert witness in a case of alleged racial discrimination in a state university school of nursing introduced a regression of the determinants of salary of each professor for each year during an 8-year period (n= 423) with the following results with dependent varable year (year in which the salary observed) and predictors year
See the attached file. Predictor Coef StDev Constant -150 90 X1 2000 500 X2 -25 30 X3 5 5 X4 -300 100 X5 0.60 0.15 Source DF SS MS F Regression 5 1,500.00 Error 15 Total 20 2,000.0 a. Complete the ANOVA table. b. Conduct a global test of hypothesis, using the .05 si
Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price(dollars per unit). (a) Write the fitted re
Prepare a report using Excel as your processing tool to process three simple regression analyses. 1. First run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the data set as the dependent variable.
Below are fitted regressions based on used vehicle ads. Observed ranges of X are shown. The assumed regression model is AskingPrice = f (Vehicle Age). (a) Interpret the slopes. (b) Are the intercepts meaningful? Explain. (c) Assess the fit of each model. (d) Is a bivariate model adequate to explain vehicle prices? If not, what
Statistics Find the regression equation, letting the first variable be the independent (x) variable. Find the indicated predicted values. Caution: When finding predicted values, be sure to follow the prediction procedure described in the section. Appendix B Data Set: Discarded Plastic and Household Size Refer to Data Set 1
Residual Plot: Consider the data in the table below. A. Examine the data and identify the relationship between x & y. B. Find the linear correlation coefficient & use it to determine whether there appears to be a significant linear correlation between x & y. C. Construct a scatter plot. What does it suggest about the relatio
Compare and contrast quantitative and qualitative research designs. Identify and discuss some advantages and disadvantages for each type of research.
Please assist with a 5-step hypothesis test on the slope of a linear regression line. I have the scatter plot, line of best fit (including equation of the line). But I don't know how to test a hypothesis for the slope of a linear regression. also explain if there is a 5-step hypothesis test for the correlation coefficient by
Find the equation of the regression line for the given data. Use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown below. Calories, X 160 170 130 130 90 180 Sodium, Y 415
Imagine you are a real estate investor presented with a regression analysis of home sales near one of your investment properties. Use Stat tools regression mod3l to determine: Which is a better predictor of selling price:appraised value, square footage, or number of bedrooms? A) How much value is added per $1000 OF APPR
Using Excel as your processing tool, work through three simple regression analyses. 1. First run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a
Richard Ellis, the director of cost operations of American Micro Devices, wishes to develop an accurate cost function to explain and predict support costs in the company's printed circuit board assembly operation. Mr. Ellis is concerned that the cost function that he currently uses? based on direct labor costs?is not accurate en
Problem: Do Hispanics earn more than white individuals at a large company, for which lawsuit filed. Attached data include, 1. Employee ID, 2. Job title, 3. Ethnicity, 4. Yrs. Working. 1. Is pay different by ethnicity and if so are they statistically significant, and what is meaning of such. Consider some of the arguments t
Hi, I need help with this assignment. I am using a different Dataset then what is in the solution library. My data set is 0903A.Xls.My school uses Turn it which is a similarity score and if it matches too high The assignment mentions a DATA SET 903A which i have provided - I have attached this information. Thank you and ple
Bus Inc. sells widgets. Sales dept says there is a positive linear relationship between the advertising expenditures and sales. Sales department recently analyzed the sales over 42 weeks. For each week in the sample, Bus Inc sales (SALES) and their advertising expenditures (ADVERT) were recorded. A simple regression analysis was
3 pages Details: Using Excel as your processing tool, work through 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
Suppose r = 0. What is the slope (provide your answer both as a calculation and a description of what the slope of the regression line would look like)? What is the y-intercept (provide your answer as a calculation)? Why does your answer for the y-intercept make sense?
An agent for a residential real estate company in a large city would like to be able to predict the monthly rental cost of apartments based on the size of the apartment.At the .05 level of significance determine if the correlation between rental cost and apartment size is significant? Rent Size 950 850 1600 1450 1200 1085 1