Answered: Unstandardized Residual 100 -100 500…

Math

Statistics

Unstandardized Residual 100 -100 500 1000 1500 Income 2000 2500 3000

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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why the correct answer is letter b?
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Television Gross Newspaper Advertising Advertising ($1,000s) ($1,000s) Revenue ($1,000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 1 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) y = 88.64 + 1.60x1 X (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s, x₂ represent the amount of…
Explain what a residual is and how this relates to the best-fit regression model.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
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You have gathered data from a random sample of fast-food sandwiches in order to better understand how the amount of fat in these sandwiches relates to the amount of carbohydrates in the sandwiches. Your ultimate goal is to construct a regression equation to predict amount of carbohydrates based on amount of fat. If this is your goal, which variable should you put on the vertical axis (or y-axis) of a scatterplot of this data? O When conducting a regression analysis, it makes no difference which variable is on which axis. O Amount of fat, because it is the explanatory variable. O Amount of carbohydrates, because it is the explanatory variable. Amount of carbohydrates, because it is the response variable. O Amount of fat, because it is the response variable.
Give examples of where the use of regression analysis can be benificially be made.
Q1: [Regression and Correlation] The index of biotic integrity (IBI) is a measure of water quality in streams. As a data analyst you must monitor, track, and predict changes in water quality. You want to create a simple linear regression model that will allow you to predict changes in IBI in forested area. The following table conveys sample data from a coastal forest region and gives the data for IBI and forested area in square kilometers. Let forest area be the predictor variable (x) and IBI be the response variable (y). IBI X 47 72 21 72234 19 58 49 Forest Area Y 38 59 27 24 63 49 45 Required a. Q2: [Naïve Bayes] a. Write the pseudo-code of the following Naïve Bayes algorithm b. Consider the given dataset that classifies animals into two distinct classes. The classes are labeled as 'cat' and 'dog'. Use Naive Bayes classifier to figure out the class (cat/dog) of an instance if it has the following values of attributed Plot Scatter graph b. Determine the regression equation c. Compute…
An online retailer examined their transactional database to see how the value of total annual purchases ($) for individual customers was related to their annual income ($). They obtained the following regression model:Total annual purchases = -49.80 + 0.0246(annual income)correlation = 0.533(a) What does the slope tell us? (Annual Income/ Total Annual Purchases) is/are predicted to increase by ($0.0246 / -$49.80) for each additional $1 of (Annual Income/ Total Annual Purchases).(b) What does the intercept tell us? A.The intercept does not have a practical meaning in this context. B. Total annual purchases are predicted to be $0.0246 when annual income = 0. C. Total annual purchases are predicted to be $-49.80 when annual income = 0. D. Annual income is predicted to be $0.0246 when total annual purchases = 0. E. Annual income is predicted to be $-49.80 when total annual purchases = 0. (c) Which statement is correct concerning the quality of this model? A. 28.4% of the variability in…
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B b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a positive linear relationship between a = average number of passing yar and y = the percentage of games won by the team. c. Develop the estimated regression equation that could be used to predict the percentage of games won given the avera passing yards per attempt. Enter negative value as negative number. WinPct =| |)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately So, for every increase : of one yar number of passes per attempt, the percentage of games won by the team increases by %. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 5.5. Use th regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs.…