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Regression Analysis

Regression analysis for fishing data

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: Hours at lake 2 3 2 1 4 5 Number of fis

Linear trend, least-square, regress equation & linear programs

1. The league of American Theatres and producers, Inc, collects a variety of statistics for Broadway plays, such as gross revenue, playing time, and number of new productions. The following data show the season attendance ( in millions) for Broadway shows from 1990 to 2001 ( the world almanac 2002) Season Attendance (in milli

Linear Regression and Correlation Hypothesis Test

53. The following data show the retail price for 12 randomly selected laptop computers along with their corresponding processor speeds in gigahertz. Computer Speed Price Computer Speed Price 1 2.0 2,689 7 2.0 2,929 2 1.6 1,229 8 1.6 1,849 3 1.6 1,419 9 2.0 2,819 4 1.8 2,589 10 1.6 2,669 5 2.0 2,849 11 1.0 1,249 6 1.2 1

Statistics: Length of bolts, simple regression analysis

34. In a manufacturing process a random sample of 9 bolts manufactured has a mean length of 3 inches with a variance of 0.09. What is the 90% confidence interval for the true mean length of the bolt? A) 2.8355 to 3.1645 inches B) 2.5065 to 3.4935 inches C) 2.4420 to 3.5580 inches D) 2.8140 to 3.8160 inches E) 2.9442

Regression Analysis of Baseball Data Set

See data file attached. Use the numerical data from the baseball data set (attached). For this assignment, you must have a hypothesis and have at least one independent variable (x) and the dependent variable (y) measured at the interval level. The assignment does not specify the type of regression used, so either bivariate or

Regression Analysis and Hypothesis Test

35. A regional commuter airline selected a random sample of 25 flights and found that the correlation between the number of passengers and the total weight, in pounds, of luggage stored in the luggage compartment is 0.94. Using the .05 significance level, can we conclude that there is a positive association between the two vari

Explained and unexplained variation and the least-squares regression line

Explained and unexplained variation and the least-squares regression line Bivariate data obtained for the paired variables and are shown below, in the table labelled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this

Regression analysis :Least squares methods

An electric utility wishes to examine the relationship between temperature and electricity use in its service region during the summer months. The bivariate data below give the maximum temperature (denoted by x, in degrees Fahrenheit) and the electricity use (denoted by ,y in thousands of kilowatt hours) for a random sample of f

Statistics: Example of regression analysis in your work. Give the model

Once we start to think about it, regression is useful in many different situations. Give an example of how you might use regression analysis in your work. As part of your answer give the model you would use and explain why you chose the specific independent variables given in your model. I own my own janitorial company.

Statistics: Simple regression of tree height on bark thickness

32) Two models were proposed for a simple regression of tree height on bark thickness, Model A: Height' = 7.8*Bark + 37 and Model B: Height' = 8*Bark + 35. Using the information and calculations below, which model is best? Model A: Height' = 7.8*Bark + 37 Tree ID Height (feet) Bark Thickness (millimeters) Predicted Hei

Houston weather data: regression equation, R-squared, intercept meaning

Instructions: ? Write the regression equation ? What does R-squared value tell you? ? What meaning does intercept have? ? Which is warmer, a day with rain or a day without? ? Is KIAH_Precip a good predictor? ? Describe fit of regression It might be supposed that rainy days would tend to be cooler than

ANOVA: Two-Factor Without Replication and Regression Analysis

Question 1: A manufacturing company designed an experiment to determine whether the number of days necessary to develop a new product depends on whether the development processes were performed sequentially or simultaneously (the method of development). Because the duration of development would depend on whether the new produ

Statistics questions

1.A random sample of 48 days taken at a large hospital shows that an average of 38 patients was treated in the emergency room per day. The standard deviation of the population is 4. Find the 99% confidence interval of the mean number of ER patients treated each day at the hospital. 2.Using the same information as in ques

Regression, Correlation, Point Estimate

[Data attached] 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. Data for a sample of 25 apartments in a particular neighborhood are provided in the attached excel spreadsheet. 1. At the .05 level of

Regression equation to predict father's education from mother's education

Run a regression equation to predict father's education from mother's education (variable paeduc and maeduc). Include 95% confidence intervals for the slop and intercept. Save the standard error of the mean prediction. Based on this equation answer the following: a. What do you predict for father's education for all people wh

Statistics Hypothesis Statement to test linear regression analysis

See attached data file. I need to formulate a hypothesis statement which can be tested with linear regression analysis using the attached data set. Legend for the data set is posted below: X1: Account Balance in dollars X2: Number of ATM transactions in the month X3: Number of other bank services used X4: Has a de

Statistics Correlations: Sales of pet food

The marketing manager of a large supermarket chain would like to use shelf space to predict the sales of pet food. For a random sample of 12 similar stores, she gathered the following information regarding the shelf space, in feet, devoted to pet food and the weekly sales in hundreds of dollars. Use these data to answer questi

Analysis of Variance Test

It has been reported that 10.3% of U.S. households do not own a vehicle, with 34.2% owning 1 vehicle, 38.4% owning 2 vehicles, and 17.1% owning 3 or more vehicles. The data for a random sample of 100 households in a resort community are summarized in the frequency distribution below. At the 0.05 level of significance, can we rej

Correlation and Regression

11A is a plot and regression analysis question from Norius Chapter 20, concept exercise # 4. I do not have this as a digital copy yet, so if you choose to accept this job, I will scan the problem and email. 11B Using the Graphs menu, make a scatterplot of husband's education against wife's education (variables husbeduc and


A)Show the scatter diagram and explain whether it displays a linear relationship. b)Enter the regression equation c)Interpret the coefficients in the regression. d)Predict the amount of ice cream sold for one day with a temperature of 950C.

Linear Demand Regression

A linear demand regression model found the following: Ordinary Least Squares Estimates ______________________________________________ Dependent Variable : QUANTITY Independent variable : Coefficient t-statistic Constant 10 2.5 - PRICE

Regression Analysis in Excel.

The file attached contains data on 80 colleges and universities. Among the variables included are the academic calendar type (1 = semester: 0 = other). Annual total cost (in thousands of dollars), average total score on the Scholastic Aptitude Test (SAT), room and board expenses (in thousands of dollars), whether the institu

Regression analysis in excel.

A sociologist theorized that people who watch television frequently are exposed to many commercials, which in turn leads them to buy more, and finally increasing their debt. To test this belief, a sample of 430 families were drawn. For each, the total debt (D) and the number of hours the tv (T) is turned on per week were recorde

Regression analysis: market specialist is analyzing household budget data

A market specialist is analyzing household budget data collected by her firm. The specialist's dependent variable is monthly household expenditures on healthcare (in $'s), and her independent variable is annual household income (in $1,000's). Regression analysis of the data yielded the following tables. Coefficients Standard