During randomization for sampling or experiment lay-outs, ensuring interspersionmeans: a. Repeating the randomization to get a satisfactory interspersion b. Resorting to haphazard arrangement instead of randomization c. All of the choices given are appropriate d. none of the choices given are appropriate e. making your own lay-out if the randomization results are not satisfactory f. Accepting any randomization outcome

Nationally, about 11% of the total U.S. wheat crop is destroyed each year by hail.† An insurance company is studying wheat hail damage claims in a county in Colorado. A random sample of 16 claims in the county reported the percentage of their wheat lost to hail. 16 6 8 9 10 18 14 13 9 10 25 18 13 8 14 3 The sample mean is x = 12.1%. Let x be a random variable that represents the percentage of wheat crop in that county lost to hail. Assume that x has a normal distribution and σ = 5.0%. Do these data indicate that the percentage of wheat crop lost to hail in that county is different (either way) from the national mean of 11%? Use ? = 0.01. (a) What is the level of significance?   Compute the z value of the sample test statistic. (Round your answer to two decimal places.)(c) Find (or estimate) the P-value. (Round your answer to four decimal places.)

Consider the experiment of tossing a coin twice...please check my work   List the experimental outcomes. Let H=Heads & T=Tails Define a random variable that represents the number of heads occurring on the two tosses. Show what value the random variable would assume for each of the experimental outcomes.

According to the Federal Trade Commission report on consumer fraud and identity theft, 23% of all complaints in 2007 were for identity theft. This year, a certain state kept track of the number of its 1325 complaints were for identity theft. They want to know if the data provide enough evidence to show that this state had a different proportion of identity theft than 23%? State the random variable, population parameter, and hypotheses. Fill in the correct null and alternative hypotheses. H0:H0:                    HA:HA:                     A Type I error in the context of this problem would be                A Type II error in the context of this problem would be

Randomization-The difference between the two sample proportions is 0.0408. Results vary but this is​ typical: Among 1000​ resamplings, differences less than or equal to −0.0408 occurred 343 times and differences greater than or equal to 0.0408 occurred 413 times. Bootstrapping-Results vary but this is​ typical: 80​% ​CI: −0.173<p1−p2<0.095.

Conduct a test at the a = 0.01 level of significance by determining (a) the null and alternative hypotheses, (b) the test statistic, and (c) the P-value. Assume the samples were obtained independently from a large population using simple random sampling. Test whether p, > P2. The sample data are x, =118, n, = 258, x, = 139, and n, = 314.

Create a research hypothesis that would be answered using either a z- or a t- test. I was thinking of doing a study on college students and the amount of articles they read in one year. Include the following: Introduction: Brief description of the study including the purpose and importance of the research question being asked. What is the null hypothesis? What is the research hypothesis? Participants/Sampling Method: Describe your sampling method. What is your sample size? Who is your population of interest? How representative is the sample of the population under study? Data Analysis: Describe the statistical analysis. What is your variable? What is its level of measurement? What is your alpha level? Results & Discussion: Did you reject the null hypothesis? What information did you use to lead you to your conclusion? Was your p value greater than or less than your alpha? NOTE: You can just make up numbers, but include your made-up p value