What's the p-value In an attempt to develop a model of wine quality as judged by wine experts, data on alcohol content and wine quality was collected from variants of a particular wine. From a sample of 17 wines, a model was created using the percentages of alcohol to predict wine quality Fromthe results of that regression, b, 0.2777 and Sp₁ = 0.1057.a. At the 0.05 level of significance, is there evidence of a linear relationship between the percentage of alcohol and wine quality?b. Construct a 95% confidence interval estimate of the population slope. B₁.a. Determine the hypotheses for the test. Choose the correct answer below.✔A. Ho B₁ = 0H₁: B, 70OD. Ho B, 20H₁: B, <0Compute the test statistic.STAT2.63(Round to two decimal places as needed.)Identify the p-value of the test statistic.p-value=(Round to three decimal places as needed.).OB. Ho Po≤0H₁ Po>0O E. Ho B, ≤0H₁ B₁>0OC. Ho Bo20OF. Ho Bo=0

a)This is a two-tailed test since the alternative hypothesis H1 contains the inequality symbol ≠.…

Answered: In an attempt to develop a model of…

Essentials Of Business Analytics

1st Edition

ISBN:9781285187273

Author:Camm, Jeff.

Publisher:Camm, Jeff.

Chapter4: Linear Regression

Section: Chapter Questions

Problem 14P: A study investigated the relationship between audit delay (the length of time from a companys fiscal...

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A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 156 students who took the course last semester are provided in the tile MktHrsPts. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between total points earned and hours spent studying? Develop an estimated regression equation showing how total points earned is related to hours spent studying. What is the estimated regression model? Test whether each of the regression parameters β0 and β1 is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? How much of the variation in the sample values of total point earned does the model you estimated in part (b) explain? Mark Sweeney spent 95 hours studying. Use the regression model you estimated in part (b) to predict the total points Mark earned.
Assume that Dylan Lee found two deviations in a sample of 90 transactions. Using AICPAsample evaluation tables, Lee determined that the ULRD at a 5 percent risk of overrelianceisa. 2.0 percent.b. 2.2 percent.c. 5.9 percent.d. 6.9 percent
A study investigated the relationship between audit delay (the length of time from a companys fiscal year-end to the date of the auditors report) and variables that describe the client and the auditor. Some of the independent variables that were included in this study follow: A sample of 40 companies provided the following data: a. Develop the estimated regression equation using all of the independent variables included in the data. b. Test for an overall regression relationship at the 0.05 level of significance. Is there a significant regression relationship? c. How much of the variation in the sample values of delay does this estimated regression equation explain? What other independent variables could you include in this regression model to improve the fit? d. Test the relationship between each independent variable and the dependent variable at the 0.05 level of significance, and interpret the relationship between each of the independent variables and the dependent variable. e. On the basis of your observations about the relationships between the dependent variable Delay and the independent variables Quality and Finished, suggest an alternative regression equation to the model developed in part a to explain as much of the variability in Delay as possible.
Suppose you're given a data set that classifies each sample unit into one of four categories: A, B, C, the data as A = 1, B=2, C = 3, and D=4. Are the data consisting of the classifications A, B, C, and D or quantitative? Are the data consisting of the classifications A, B, C, and D qualitiative or quantitative? OA. Qualitative, because they are measured on a naturally occuring numerical scale. B. Quantitative, because they are measured on a naturally occuring numerical scale. C. Quantitative, because they can only be classified into categories. D. Qualitative, because they can only be classified into categories. *** After the data are input as 1, 2, 3, or 4, are they qualitative or quantitative? OA. Qualitative, because they cannot be meaningfully added, subtracted, multiplied, or divided. B. Qualitative, because they are measured on a naturally occurring numerical scale. OC. Quantitative, because they are measured on a naturally occurring numerical scale. OD. Quantitative, because…
The randomly selected 60 shoppers have rated a new bottle design for a popular soft drink. The data are given below. Determine the no. of classes, class width, and the relative frequency of each class to construct the histogram for the given data. Explain the skewness of data based on the histogram.
A highway department is studying the relationship between traffic flow and speed during rush hour on Highway 193. The data in the file TrafficFlow were collected on Highway 193 during 100 recent rush hours. a. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between vehicle speed and traffic flow? b. Develop an estimated simple linear regression equation for the data. How much variation in the sample values of traffic flow is explained by this regression model? Use a 0.05 level of significance to test the relationship between vehicle speed and traffic flow. What is the interpretation of this relationship? c. Develop an estimated quadratic regression equation for the data. How much variation in the sample values of traffic flow is explained by this regression model? Test the relationship between each of the independent variables and the dependent variable at a 0.05 level of significance. How would you interpret this model? Is this model superior to the model you developed in part (b)? d. As an alternative to fitting a second-order model, fit a model using a piecewise linear regression with a single knot. What value of vehicle speed appears to be a good point for the placement of the knot? Does the estimated piecewise linear regression provide a better fit than the estimated quadratic regression developed in part (c)? Explain. e. Separate the data into two sets such that one data set contains the observations of vehicle speed less than the value of the knot from part (d) and the other data set contains the observations of vehicle speed greater than or equal to the value of the knot from part (d). Then fit a simple linear regression equation to each data set. How does this pair of regression equations compare to the single piecewise linear regression with the single knot from part (d)? In particular, compare predicted values of traffic flow for values of the speed slightly above and slightly below the knot value from part (d). f. What other independent variables could you include in your regression model to explain more variation in traffic flow?
Five observations taken for two variables follow. a. Develop a scatter diagram with x on the horizontal axis. b. What does the scatter diagram developed in part a indicate about the relationship between the two variables? c. Compute and interpret the sample covariance. d. Compute and interpret the sample correlation coefficient.
Identify the factors an auditor uses to decide the appropriateARO. Compare the sample size for an ARO of 10% with that of 5%, all other factorsbeing equal.
Sample Size Determination. For each of the following independent cases, use AICPA sample size tables to identify the missing value(s). Control 1 2 3 4 Risk of overreliance 5.0% 5.0% 10.0% (d) Expected population deviation rate 1.25% 2.5% (c) 1.25% Tolerable rate of deviation 7.0% (b) 6.0% 6.0% Sample size (a) 68 153 78
Evaluating Results: Classical Variables Sampling. Kyle Berry is using mean-per-unit estimation in the audit of Leonard’s inventory balances. Leonard’s inventory is recorded at $240,000 and comprises 1,200 different items. Berry determined a sample size of 120 items and performed the appropriate substantive procedures. Based on this sample, he determined the following: Average audited value (per item) $204 Standard deviation of audited values $ 22 A summary of some additional parameters estimated by Berry follow: Tolerable misstatement $ 17,500 Expected misstatement $ 7,500 Risk of incorrect acceptance 5% Risk of incorrect rejection 10% Required:a. What is Berry’s estimate of the audited value of Leonard’s inventory?b. Calculate the precision and precision interval for Leonard’s inventory. Provide a briefdescription of the meaning of the precision interval.c. What is Berry’s conclusion with respect to Leonard’s inventory balance?d. Using a risk of incorrect…
Assume there are 3,600 cases in the validation dataset, and 12% of these cases have a value of 1 for churn (the primary/positive event). Questions a) to c) are based on data for the 3,600 cases (see table below). Depth (% Contacted) Model Cumulative Gain Cumulative Lift Decision Tree 34.42 6.84 Logistic Regression Neural Network 20.19 4.01 34.62 6.88 Decision Tree Logistic Regression Neural Network 10 64.90 6.06 10 36.06 3.15 10 62.50 5.54 Decision Tree 15 73.96 1.82 Logistic Regression Neural Network 15 49.04 2.62 15 82.21 3.97 Decision Tree Logistic Regression 20 78.39 0.87 20 59.13 2.01 Neural Network 20 86.54 0.86 a) Which model has the highest Cumulative Lift at a depth of 20%? What is the lift? b) If the Cumulative Gain at a depth of 10% for the Decision Tree is converted to number of primary/positive event cases, what will be the number of cases? Show your calculation. c) If the Cumulative Gain at a depth of 15% for the Neural Network model is converted to number of…
An auditor is determining the appropriate sample size for testing inventory valuation using MUS The population has 3,140 inventory items valued at Calculate the preliminary sample size. Select the formula, then enter the amounts and calculate the sample size. (Abbreviation used TM tolerable misstatement Enter amounts in the for (Click the icon to view the table for determining the confidence factor) Confidence Factor 4.33 TM as Percentage of Population Value 39.75 ECCEED Sample Size

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