For Exercises 5–8: (a) State the null hypothesis and the alternate hypothesis. (b) State the decision rule. (c) Compute the value of the test statistic. (d) What is your decision regarding H0? (e) What is the p-value? Interpret it.
5. The manufacturer of the X-15 steel-belted radial truck tire claims that the
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Statistical Techniques in Business and Economics
- Do people walk faster in the airport when they are departing (getting on a plane) or do they walk faster when they are arriving (getting off a plane)? A reputable researcher measured the walking speed of random travelers in two International Airports. His findings are summarized in the table. Complete parts (a)-(c) below. Click the icon to view the findings. Walking Speed - X Direction of Travel Departure Mean speed 254 Arrival 267 = 0.05 level of significance? Let μ₁ represent the mean speed of people departing and H2 represent the mean speed of (feet per minute) Standard 47 38 deviation (feet Print Done Determine the P-value for this hypothesis test. P-value = (Round to three decimal places as needed.) B. Ho: H1 H2 H₁: H₁>H₂ D. Ho: H1 H2 H₁: H1 H2.arrow_forwardUsing image attached A. Fill in blanks B. What are the null and alternative hypothesis? C. Find the test statistic, z0 D. Find the P-Valuearrow_forwardDescribe type I and type II errors for a hypothesis test of the indicated claim. A clothing store claims that at least 80% of its new customers will return to buy their next article of clothing. Describe the type I error. Choose the correct answer below. OA. A type I error will occur when the actual proportion of new customers who return buy their next article of clothing is at least 0.80, but you reject Ho: p20.80. OB. A type I error will occur when the actual proportion of new customers who return to buy their next article of clothing is at least 0.80, but you fail to reject Ho: p20.80. OC. A type I error will occur when the actual proportion of new customers who return article of clothing is no more than 0.80, but you fail to reject Ho: p≤0.80. OD. A type I error will occur when the actual proportion of new customers who return article of clothing is no more than 0.80, but you reject Ho: p≤0.80. buy their next buy their nextarrow_forward
- Answer all sub parts otherwise I will dislikearrow_forwardYou are a consumer psychologist interested in holiday spending. A national census reports that the American family spent an average of µ = $81 for Halloween candy and costumes last year. A sample of N = 16 families this year produced a mean of $85 with s = 20. t-value ? t-critical?arrow_forwardwoman loves, as everyone should, to collect and analyze statistical information. He wishes to find a relationship between how many hours students study and how they do on their statistics tests. He takes a random sample of 16 students at Ideal U., asks how many hours they studied for a university-wide stat testand how they did on the test, enters the data into a computer for analysis and presents the results below. ANALYSIS OF HOURS AND GRADES (n = 16): Descriptive Statistics: HOURS GRADES Mean: 4.2 75.8 Mode: 5.0 79.0 St. Dev: 2.3 10.1 Quartiles: Q0 2.0 34.0 Q1 3.2 53.7 Q2 4.7 78.5 Q3 6.3 86.9 Q4 9.0 97.0 Regression Analysis: Reg. Eq. is: GRADE = 16.9 + 9.025*HOURS Rsquared = .985 std error = 0.027 F = 8.52 p = .018 What is the correlation between hours studied and grades? a. 0.016 b. 0.992 c. 0.985 d. cannot be determined e. 0.12arrow_forward
- man loves, as everyone should, to collect and analyze statistical information. He wishes to find a relationship between how many hours students study and how they do on their statistics tests. He takes a random sample of 16 students at Ideal U., asks how many hours they studied for a university-wide stat test and how they did on the test, enters the data into a computer for analysis and presents the results below. ANALYSIS OF HOURS AND GRADES (n = 16): Descriptive Statistics: HOURS GRADES Mean: 4.2 75.8 Mode: 5.0 79.0 St. Dev: 2.3 10.1 Quartiles: Q0 2.0 34.0 Q1 3.2 53.7 Q2 4.7 78.5 Q3 6.3 86.9 Q4 9.0 97.0 Regression Analysis: Reg. Eq. is: GRADE = 16.9 + 9.025*HOURS Rsquared = .985 std error = 0.027 F = 8.52 p = .018 What is the median number of hours studied? a. 2.3 b. 4.7 c. 4.5 d. 4.2 e. 5.5 f. 5 g. cannot be determinedarrow_forwardman loves, as everyone should, to collect and analyze statistical information. He wishes to find a relationship between how many hours students study and how they do on their statistics tests. He takes a random sample of 16 students at Ideal U., asks how many hours they studied for a university-wide stat test and how they did on the test, enters the data into a computer for analysis and presents the results below. ANALYSIS OF HOURS AND GRADES (n = 16): Descriptive Statistics: HOURS GRADES Mean: 4.2 75.8 Mode: 5.0 79.0 St. Dev: 2.3 10.1 Quartiles: Q0 2.0 34.0 Q1 3.2 53.7 Q2 4.7 78.5 Q3 6.3 86.9 Q4 9.0 97.0 Regression Analysis: Reg. Eq. is: GRADE = 16.9 + 9.025*HOURS Rsquared = .985 std error = 0.027 F = 8.52 p = .018 We know that 25% of all the grades falls into which of these regions? a. 78.5 to 79.0 b. 78.5 to 86.9 c. 75.8 to 86.9 d. 75.8 to 97.0 e. 78.5 to 97.0 f. 75.8 to 79.0arrow_forwardman loves, as everyone should, to collect and analyze statistical information. He wishes to find a relationship between how many hours students study and how they do on their statistics tests. He takes a random sample of 16 students at Ideal U., asks how many hours they studied for a university-wide stat test and how they did on the test, enters the data into a computer for analysis and presents the results below. ANALYSIS OF HOURS AND GRADES (n = 16): Descriptive Statistics: HOURS GRADES Mean: 4.2 75.8 Mode: 5.0 79.0 St. Dev: 2.3 10.1 Quartiles: Q0 2.0 34.0 Q1 3.2 53.7 Q2 4.7 78.5 Q3 6.3 86.9 Q4 9.0 97.0 Regression Analysis: Reg. Eq. is: GRADE = 16.9 + 9.025*HOURS Rsquared = .985 std error = 0.027 F = 8.52 p = .018 What problem might there be in using the regression model to predict what grade a student might get if they studied 10 hours? a. The predicted grade for 10 hours is more than 100, which is impossible. b. The value of 10…arrow_forward
- just the multiple choice partarrow_forwardProfessor Gersch loves, as everyone should, to collect and analyze statistical information. He wishes to find a relationship between how many hours students study and how they do on their statistics tests. He takes a random sample of 16 students at Ideal U., asks how many hours they studied for a university-wide stat test and how they did on the test, enters the data into a computer for analysis and presents the results below. ANALYSIS OF HOURS AND GRADES (n = 16): Descriptive Statistics: HOURS GRADES Mean: 4.2 75.8 Mode: 5.0 79.0 St. Dev: 2.3 10.1 Quartiles: Q0 2.0 34.0 Q1 3.2 53.7 Q2 4.7 78.5 Q3 6.3 86.9 Q4 9.0 97.0 Regression Analysis: Reg. Eq. is: GRADE = 16.9 + 9.025*HOURS Rsquared = .985 std error = 0.027 F = 8.52 p = .018 Based on the regression model, what grade would a student get if they studied 10 hours? a. 90.25 b. 107.15 c. 97.0 d. 16.9arrow_forwardState whether the standardized test statistic t indicates that you should reject the null hypothesis. Explain. (a) t= 1.584 (b) t=0 (c) t= - 1.526 (d) t= - 1.604 to = - 1.558 (a) For t= 1.584, should you reject or fail to reject the null hypothesis? O A. Fail to reject Ho, because t> - 1.558. O B. Reject Ho, because t> - 1.558. O C. Reject Ho, because t - 1.558. O B. Fail to reject Ho, because t - 1.558. (c) For t= - 1.526, should you reject or fail to reject the null hypothesis? O A. Reject Ho, because t - 1.558. O C. Fail to reject Ho, because t> - 1.558. O D. Fail to reject Hn, because t< - 1.558.arrow_forward
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