Use NCSS to conduct all statistical tests and calculations. For each question, you are to edit, copy, paste and highlight the appropriate output from NCSS and produce a typed document answering the questions. Be succinct. Control the Type I error rate at the 0.05 level for all statistical test procedures and confidence interval
1) John is an avid fisherman and wants to know if there is a correlation between the amount of time he spends fishing and the amount of fish he catches. He decided to keep track of the time he spent at the lake and the amount of fish he caught. The results were as follows: Week 1 2 3 4 5 6 Hours at lake 2 3 2 1 4 5 Fish
File with full description attached... Linear Regression Analysis The housing market is no stranger to trends and how those trends affect every aspect of that market. The trends are common factors that occur over a time period and that element is what regression and the trend method focus on. Trends are ever changing and thi
The following data show U.S. production of motor vehicles versus tons of domestic steel shipped for motor vehicle manufacture. Year X=U.S. Production of Motor Vehicles Y=Tons of Domestic Steel 2000 12.83 million 16.06 million 2001 11.52 14.06 2002 12.33 14.0 2003 12.15 15.88 2004 12.02 13.86 a. Determine the least-squar
For each of 10 popular prescription drugs, file XR15042 lists the retail price (in U.S. dollars) for the drug in several different countries, including the United States, Canada, Great Britain, and Australia. Determine and interpret the coefficients of correlation and determination for U.S. prices versus Canadian prices.
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 variable. Create a
For the y and x values listed in file XR15066, obtain the simple linear regression equation, then analyze the residuals by (a) constructing a histogram, (b) using a normal probability plot, (c) plotting the residuals versus the x values and (d) plotting the residuals versus the order in which they were observed. Do any of the as
For the leading health maintenance organization (HMO) firms, the attachment lists the number of persons enrolled in the HMO along with the number of plans that firm administers. Given these dates, determine the least-squares equation for predicting the total enrollment as a function of the number of plans administered. What woul
The following data represent x = boat sales and y = boat trailer sales from 1995 through 2000.0 Year Boat sales (thousands) Boat trailer sales (thousands) 1995 649 207 1996 619 194 1997 596 181 1998 576 174 1999 585 168 2000 574 159 a. determine that least-squares regression line and interpret its slope b. estimate,
My brother would like to retire and move to a quieter place, probably away from me. I suggested area around Lake Louise. But he had a more remote location in mind...... He did some housing market research in a secret destination, and would like to have me taking a look at his data. Square Footage Asking Price (Canadian
In these two exercises, construct a scatter plot, find the value of the linear correlation coefficient r, find the critical value of r from Table A-6 by using α = 0.05, and determine whether there is a linear correlation between the two variables. Song Audiences and Sales The table below lists the numbers of audience
Please see attached. According to the Capital Asset Pricing Model (CAPM), the risk associated with a capital asset is proportional to the slope ß obtained by regressing the asset's past returns with the corresponding returns of the average portfolio called the market portfolio. (The return of the market portfolio represents
Please make up a simple regression analysis "application" example. For the "application" example submit both your manual and excel stats functional work for testing hypothesis H0: beta 1=0 (by using t test). A typical simple regression analysis "application" example is as follows: The following data are the height, in inches,
3. Given are five observations collected in a regression study on two variables. X1 | 2 6 9 13 20 Y1| 7 18 9 26 23 a. Develop a scatter diagram for these data. b. Develop the estimated regression equation for these data. c. Use the estimated regression
1. The least squares regression line given above is said to be a line which "best fits" the sample data. The term "best fits" is used because the line has an equation that minimizes the ______, which for these data is______. 2. For the data point (225.3, 308.1), the value of the residual is_____. (Round your answer to at le
After deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers calculate the equation of the least squares regression line to be Yhat = 2492.09 - 10.48X. 1) For these data, coffee sales values that are greater than the meand of the coffee sales values tend to be paired with
(a) List two limitations of a bivariate regression. (b) Why is estimating a multiple regression model just as easy as bivariate regression?
Recently, students in a marketing research class were interested in the driving behavior of students. Specifically, the marketing students were interested if exceeding the speed limit was related to gender. They collected the following responses from 100 randomly selected students:
1. The following time series data represent the yearly amounts spent on advertising (in millions of dollars) by a large toy company: 29.5, 28.6, 34.2, 34.6, 39.3, 35.6, 43.1, 40.4, 50.1, 50.1 This series of data begins in year (i.e., time period corresponds to ). Using regression analysis, a linear trend line of the form
The monthly number of permits granted for building houses in a large city is seasonal (there tend to be more permits granted for construction during spring and summer months than during winter months). The following table shows the monthly seasonal indexes for building permits: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Complete a Bivariate Regression Problem including: scatter plot, correlation coefficient, t-test for coefficient.
Instructions for Exercises 12.4-12.6: (a) Make a scatter plot of the data. What does it suggest about the correlation between X and Y? (b) Use Excel, MegaStat, or MINITAB to calculate the correlation coefficient. (c) Use Excel or Appendix D to find t.05 for a two-tailed test. (d) Calculate the t test statis
Create a hypothesis statement from a data set regarding two variables and perform a regression analysis.
Using numerical data from attached data set, formulate a hypothesis which can be tested with linear regression analysis. Perform a regression analysis to test your hypothesis.
Using regression analysis determine if there is a correlation between the amount of time spent fishing and the amount of fish caught.
John is an avid fisherman and wants to know if there is a correlation between the amount of time he spends fishing and the amount of fish he catches. He decided to keep track of the time he spent at the lake and the amount of fish he caught. The results were as follows: Week 1 2 3 4 5 6 Hours at lake 2 3 2 1 4 5 Fi
Given bi-variate data construct a scatterplot, fit a regression line to the data, and plot the residuals... (please see attached file for problem description)
Please see attached file for problem description. a). Make a scatterplot of these data (in excel). The relationship appears to be approximately linear, but the wide variation in the response values makes it hard to see detail in this graph. b). Compute the least-squares regression line of y on x, and plot this line on your
1. If the sample size is 36 with three treatment means (response variables) and you are performing an ANOVA, then the degrees of freedom for the error term will be: 2. If the least squares equation for sales data is the following: Y = 10 + 1.3 X (in $ millions) what are the sales when X = 10 (in millions of dollars)? 3.
I need help in determining the co-efficient of determination for the above hypothesis using the correlation/regression analysis. The data sheet used is below: Literacy % Life Expectancy 1 52.0 62.7 2 57.1 51.1 3 58.0 67.0 4 61.6 70.0 5 62.8 68.1 6 72.1 70.0 7 76.2 75.7 8 78.6 76.3 9 79.0 72.6 10 79.2 74.3 11 81.1
Below are four bivariate data sets and the scatter plot for each. (Note that each scatter plot is displayed on the same scale.) Each data set is made up of sample values drawn from a population. Please see the attachment.
Please see the attached file. The scatter-plot above shows the proportion of perch eaten by bass against the number of perch in a pen before the bass were let in. There is a roughly linear pattern. The least-squares line for predicting proportion eaten from initial count of perch is: Proportion eaten= 0.120 + (0.0086 x count
Multiple regression equation. Given the computer output from a regression analysis, write the regression equation, describe the variables, and decide of some of the variables should be eliminated from the equation.
Thompson Machine Works purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Four variables were listed. X1 = Length of time employee was a machinist X2 = Mechanical aptitude test score X3 = Prior on -the-job rating X4 = A
Regression analysis of free throws by 29 NBA teams during the 2002-2003 season revealed the fitted regression Y = 55.2 + .73X (R2 = .874, Sxy = 53.2) where Y = total free throws made and X = total free throws attempted. The observed range of X was from 1,620 (New York Knicks) to 2,382 (Golden State Warriors). a) Find the expect