Any basketball fan knows that Shaquille O’Neal, one of the NBA’s most dominant centers of the last twenty years, always had difficulty shooting free throws. Over the course of his career, his overall made free-throw percentage was 53.3%. During one off-season, Shaq had been working with an assistant coach on his free-throw technique. During the next season, a simple random sample showed that Shaq made 26 of 39 free-throw attempts. Test

A psychologist wanted to know if students in her class were more likely to cheat if they were low achievers. She divided her 60 students into three groups (low, middle, and high) based on their mean exam score on the previous three tests. She then asked them to rate how likely they were to cheat on an exam if the opportunity presented itself with a very limited chance for consequences. The students rated their desire to cheat on a scale ranging from 1-100, with lower numbers indicating less desire to cheat.   Before opening the data, what would you hypothesize about this research question?   Open the data set. Before running any statistical analyses, glance through the data. Do you think that your hypothesis will be supported?   Conduct descriptive analyses and report them here.   Conduct a one-way ANOVA. Report your statistical findings (including any applicable tables in APA format) here.   What would you conclude from this analysis? What would be your next steps, if this…

Use the following information to answer the question. Many couples believe that it is getting too expensive to host an "average" wedding in the United States. According to the website www.costofwedding.com,theaveragecostofaweddingintheU.S.in 2009 was $24,066. Recently, in a random sample of 40 weddings in the U.S. it was found that the average cost of a wedding was $23,224, with a standard deviation of $2,903. On the basis of this, a 9 5% confidence interval for the mean cost of weddings in the U.S. is $22,296 to $24,152. Does the confidence interval provide evidence that the mean cost of a wedding has decreased? Explain your reasoning.

Your statistics instructor claims that 60 percent of the students who take her Elementary Statistics class go through life feeling more enriched. For some reason that she can't quite figure out, most people don't believe her. You decide to check this out on your own. You randomly survey 55 of her past Elementary Statistics students and find that 29 feel more enriched as a result of her class. Now, what do you think?

According to the financial reports by Snapchat, the average daily user of Snapchat created 19 messages, or "snaps," per day in Q3 2017. A college student wants to find out if the number of Snapchat messages has changed since Q3 2017 and creates a random sample using information from students on her campus for the current semester, with the accompanying results. Complete parts a through Click the icon to view the daily snaps data. C. a. Using a = 0.01, test the hypothesis that the number of Snapchats sent by the average Snapchat user has not changed since Q3 2017. Determine the null and alternative hypotheses. Hot = 19 19 H₁: (Type integers or decimals. Do not round.) Determine the appropriate critical value. Select the correct choice below and fill in the answer box within your choice. (Round to three decimal places as needed.) O A. O B. -ta= OC. ±¹/2 t = t Daily Snaps G 22 13 9 18 15 33 8 23 27 27 22 31 20 16 19 33 31 5 Print 15 D 21 Done - X

If all of the students in a class earn the same score on a quiz, what should be said about the variability of the scores?

The authors of a paper randomly selected two samples of patients admitted to the hospital after suffering a stroke. One sample was selected from patients who received biofeedback weight training for 8 weeks, and the other sample was selected from patients who did not receive this training. At the end of 8 weeks, the time it took (in seconds) to stand from a sitting position and then to sit down again (called sit-stand-sit time) was measured for the people in each sample. Data consistent with summary quantities given in the paper are given below. For purposes of this exercise, you can assume that the samples are representative of the population of stroke patients who receive the biofeedback training and the population of stroke patients who do not receive this training. Biofeedback Group 2.1 2.8 4.5 2.3 2.9 4.3 3.4 4.2 3.4 3.7 3.0 3.7 3.7 2.5 3.3 No Biofeedback Group 5.2 4.8 4.0 4.3 4.8 4.4 4.3 5.2 3.5 4.3 5.2 4.5 4.1 3.5 4.0   Conduct a test of hypothesis to test whether…

Of the 328 patients that completed the survey last year, 211 of them claimed to be returning patients which is 64.3% of the sample. What type of data, quantitative or categorical, is the question “How long did you wait past your appointment time?” asking for? Justify your answer.

Kurtis is a statistician who claims that the population mean annual salary of an employee in Yarmouth is exactly $55,000. Gina, his colleague, believes this to be incorrect, and conjectures that the population mean annual salary of an employee in Yarmouth is greater than $55,000. To test the claim, Gina randomly selects 61 employees who work in Yarmouth and records their annual salary. Gina calculates the sample mean annual salary to be $56,500 per year with a sample standard deviation of $3,750. The test statistic t for a hypothesis test of H0:μ=55,000 versus Ha:μ>55,000 is t≈3.12. If p-value<0.005 and the level of significance is α=0.01, which of the following statements are accurate for this hypothesis test to evaluate the claim that the true population mean annual salary of an employee in Yarmouth is greater than $55,000? Select all that apply:   Fail to reject the null hypothesis that the true population mean annual salary of an employee in Yarmouth is equal to…

Warren wants to know if the amount of coffee that you drink is related to the number of hours that you stay awake. He recruits 50 participants using random sampling to report how much coffee they drank and the time of the day that they went to sleep. He then performs a correlation to determine the association between the amount of coffee that was consumed and the number of hours that they stayed awake. There was a statistically significant positive correlation between amount of coffee that participants drank and the number of hours that they stayed awake, r(49) = .82, p < .05, two-tailed, r2 = .08. This was a small effect – 8% of the variance in the amount of coffee drank is explained by hours that you stay awake (and vice versa).