webassign.net/web/Student/Assignment-Responses/submit?dep=33426115\&tags=autosave\#question4927711_5 PREVIOUS ANSWERS classea SIS K-12360 Launch ASK YOUR TEACHER PRACTICE ANOTHER An article about the California lottery gave the following information on the age distribution of adults in California: \( 35 \% \) are between 18 and 34 years old, \( 51 \% \) are between 35 and 64 years old, and \( 14 \% \) are 65 years old or older. The article also gave information on the age distribution of those who purchase lottery tickets. The following table is consistent with the values given in the article. Suppose that the data resulted from a random sample of 200 lottery ticket purchasers. Based on these sample data, is it reasonable to conclude that one or more of these three age groups buys a disproportionate share of lottery tickets? Use a chi-square goodness-of-fit test with \( \alpha=0.05 \). (Round your answer to two decimal places.) \begin{tabular}{|l|c|} \hline Age of Purchaser & Frequency \\ \hline \( 18-34 \) & 38 \\ \hline \( 35-64 \) & 105 \\ \hline 65 and over & 57 \\ \hline \end{tabular} \( \chi^{2}= \) \( \square \) \( P \)-value interval \( p<0.001 \) \( 0.001 \leq p<0.01 \) \( 0.01 \leq p<0.05 \) \( 0.05 \leq p<0.10 \) \( p \geq 0.10 \) The data \( \square \) provide strong evidence to conclude that one or more of the three age groups buys a disproportionate share of lottery tickets.
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- Alternative Hypothesis (Ha): At least one age group buys a disproportionate share of lottery tickets compared to their representation in the adult population. Show more…
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An article about the California lottery gave the following information on the age distribution of adults in California: 35% are between 18 and 34 years old, 51% are between 35 and 64 years old, and 14% are 65 years old or older. The article also gave information on the age distribution of those who purchase lottery tickets. The following table is consistent with the values given in the article. Suppose that the data resulted from a random sample of 200 lottery ticket purchasers. Based on these sample data, is it reasonable to conclude that one or more of these three age groups buys a disproportionate share of lottery tickets? Use a chi-square goodness-of-fit test with α = 0.05. (Round your answer to two decimal places.) Age of Purchaser | Frequency 18-34 | 40 35-64 | 120 65 and over | 40 χ² = P-value interval p < 0.001 0.001 ≤ p < 0.01 0.01 ≤ p < 0.05 0.05 ≤ p < 0.10 p ≥ 0.10 The data ---Select--- strong evidence to conclude that one or more of the three age groups buys a disproportionate share of lottery tickets. You may need to use the appropriate table in Appendix A to answer this question.
Qudsiya A.
6.41 Open source textbook: A professor using an open source introductory statistics book predicts that 60% of the students will purchase a hard copy of the book, 25% will print it out from the web, and 15% will read it online. At the end of the semester, he asks his students to complete a survey where they indicate what format of the book they used. Of the 126 students, 71 said they bought a hard copy of the book, 30 said they printed it out from the web, and 25 said they read it online. (a) State the hypotheses for testing if the professor's predictions were inaccurate. Ho: PBuy = .6, PPrint=.25, POnline=.15 Ha: at least one of the claimed probabilities is different (b) How many students did the professor expect to buy the book, print the book, and read the book exclusively online? (please do not round) Observed Expected Buy Hard Copy 71 Print Out 30 Read Online 25 (c) Calculate the chi-squared statistic, the degrees of freedom associated with it, and the p-value. The value of the test-statistic is: (please round to two decimal places) The degrees of freedom associated with this test are: (d) Calculate the p-value. Based on this, what is the conclusion of the hypothesis test? Since p > α we do not have enough evidence to reject the null hypothesis Interpret your conclusion in this context. The data do not provide sufficient evidence to claim that the actual distribution differs from what the professor expected
Suman K.
Using R script code for these questions. 1. A fire department aims to respond to fire calls in 4 minutes or less, on average. Response times are normally distributed with a standard deviation of 1 minute. Would a sample of 18 fire calls with a mean response time of 4.5 minutes provide sufficient evidence to show that the goal is not being met at the significance level α = .01? Is this a left-tailed, right-tailed, or two-tailed test? Formulate null and alternative hypothesis. Compute the appropriate test statistic and critical value using R. What is the statistical decision? Interpret the results. 2. The mean arrival rate of flights at Philadelphia International Airport is 195 flights or less per hour with a historical standard deviation of 13 flights. To increase arrivals, a new air traffic control procedure is implemented. In the next 30 days, the arrival rate per day is given in the data vector below called flights. Air traffic control manager wants to test if there is sufficient evidence that arrival rate has increased. flights <- c(210, 215, 200, 189, 200, 213, 202, 181, 197, 199, 193, 209, 215, 192, 179, 196, 225, 199, 196, 210, 199, 188, 174, 176, 202, 195, 195, 208, 222, 221) Find sample mean and sample standard deviation of arrival rate using R functions mean() and sd(). Is this a left-tailed, right-tailed or two-tailed test? Formulate the null and alternative hypothesis. What is the statistical decision at the significance level α = .01? Run the appropriate test if the population standard deviation was not known. What is the test statistic? What is the critical value? What is the statistical decision at significance level α = .01? 3. The target activation force of the buttons on a clicker is 1.967 newtons. Variation exists in activation force due to the nature of the manufacturing process. A sample of 9 clickers showed a mean activation force of 1.88 newtons. The population standard deviation is known to be 0.145 newton. Too much force makes the keys hard to click, while too little force means the keys might be clicked accidentally. We want to use an appropriate hypothesis test to detect excessive deviations in either direction. What is the appropriate hypothesis test? What is the test statistic value? At α = .05, does the sample indicate a significant deviation from the target?
Sri K.
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