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- Using ANOVA example on body temperature for different age groups, test whether these programmers commit same number of errors on average. State Ho vs Ha Test statisticSample distribution of variance follows a Chi-Square distribution with n-1 degrees of freedom True O FalseQuestion Use the random sample data to test the claim that less than 29% of local residents have access to high speed internet at home. Use 5% level of significance. • Sample data: x= 48, n= 200 1. Identify the tail of the test. [ Select] 2. Find the P-value ( Select ] 3. Will the null hypothesis be rejected? [ Select] 4. Is the initial claim supported? [ Select ]
- Chocolate Chip Cookie Calories The average 1-ounce chocolate chip cookie contains 110 calories. A random sample of 14 different brands of 1- ounce chocolate chip cookies resulted in the following calorie amounts. At the a=0.10 level, is there sufficient evidence that the average calorie content is greater than 110 calories? Assume the population is normally distributed. 100 105 160 110 Send data to Excel Part 1 of 5 (a) State the hypotheses and identify the claim. Ho: 110 claim H₁: 110 not claim This hypothesis test is a one-tailed Correct Answer: Ho: μ = 110 not claim H₁: μ> 110 claim This hypothesis test is a one-tailed test. Part 2 of 5 Correct Answer: (b) Find the critical value(s). Round the answer to three decimal places, if necessary. If there is more than one critical value, separate them with commas. Critical value(s): 2.624) Critical value: 1.350 115 115 150 120 190 120 152 100 135 153 Part: 2 / 5 Part 3 of 5 t = test. (c) Compute the test value. Round the sample statistics…Runs Test If we use a 0.05 significance level to test for randomness, what are the critical values from Table A-10? Based on those values and the number of runs from Exercise 2, what should be concluded about randomness?Analysis of Variance (ANOVA) o What is an Analysis of Variance test? o When do we use Analysis of Variance test? Nominal scale-definition and example Interval scale-definition and example o Examples of an Analysis of Variance test o Hypotheses for an Analysis of Variance test o Applying SPSS software to conduct an Analysis of Variance test o Interpreting the results of an Analysis of Variance test
- (a) Explain 3 methods of obtaining data from sampling? (b) What are two important aspects of gathering data from experimentsChi-Square Analysis The National Sleep Foundation used a survey to determine whether hours of sleeping per night are independent of age. The following shows the hours of sleep on weeknights for a sample of individuals age 49 and younger and for a sample of individuals age 50 and older. Hours of sleep Fewer than 6 6 to 8 8 or more 49 or younger 44 42 28 50 or older 38 54 73 At the 10% level of significance, explore this dataset by performing the appropriate Chi-square test. 1. Compute for the value of the test statistic. Round off your final answer to the nearest thousandths. 2. What are the appropriate hypotheses? 3. What is the critical value in the decision rule? 4. What is the appropriate conclusion?Sh/question/an-airline-offers-discounted-advance/ ADER SUBJECTS v Upper level math > Statistics question & answer logicfail2 Asked 2 yrs ago. An airline offers discounted "advance purchase " fares to customers who buy tickets more than 30 days before travel and charges "regular" fares for tickets purchased during those last 30 days. The company has noticed that 60% of its customers take advantage of the advance-purchase fares. The "no-show" rate among people who paid regular fares is 30%, but only 5% of customers with advance-purchase tickets are no-shows. a) What percent of all ticket holders are no-shows? b) What 's the probability that a customer who didn't show had an advance -purchase ticket? c) Is being a no-show independent of the type of ticket a passenger holds? Explain. 5.0 * 09 Sarah Schrijvers a) The percent of no-shows is the percent of no-shows of advance-purchase tickets increased by the percent of no-shows of advance purchase tickets: P(no-show) = 0.6 × 0.05+0.4 × 0.3…
- TEST OF HYPOTHESIS3-7 Hypothesis Test Business Nonathlete vs. National Av Business Athlete vs. National Average Proportion Sample Size (n) =count(range) 0 Response of Interest (ROI) Cheated Proportion Sample Size (n) =count(range) Response of Interest (ROI) Cheated Count for Response (CFR) Sample Proportion (pbar) =CFR/n Count for Response (CFR) =COUNTIF (range, ROI)| Sample Proportion (pbar) =CFR/nTRUE OR FALSE
