726 2047 2172 2164 1305 997 1732 2674 2497 2857 1638 2094 503

2172 1543 1130 2781 2164 2443 1236 1530 1305 2940 1805 2172 997

3402 2347 1871 1732 3975 2460 1024 1868 3285 3226 879 2047

1766 3144

The above table presents the increased of hospitalized COVID-19 patients in the United States between February 1, 2021 to March 7, 2021. Use the above information to answer A-J. Please show all work and label each question.

A.Using your knowledge in statistics, indicate the conditions under which this data set is meaningful.

B.Construct an expanded frequency distribution(class limits. class boundaries, frequency, midpoint, relative frequency and cumulative frequency) a frequency histogram, and frequency polygon of the data set using seven classes.

C.How do the different measures of center compare? (mean. Median, mode)

D.Calculate all the measures of variation of the data set (range, variance, standard deviation)

E..Calculate the measures of relative standing (quartiles, fractiles, etc) for the data set and construct its corresponding Boxplot.

F.Is this data distribution bell-shaped? Consider all the conditions and support your answer with a graph.

G.Is it unusual to have 4000 hospitalized COVID-19 patientduring the period above mentioned?

H..Find the probability that a randomly selected hospital receives between 2500 and 3500 COVID-19 patients

I.Construct a 99% confidence interval for the population mean. Assume that the data set is normally distributed.

J..A doctor claims that the average hospitalized COVID-19 patients in the US during this period is 2050. Is there enough evidence to reject the claim at(Identify the claim and state Ho and Ha, find the critical values, and identify the rejection region, decide whether to reject or fail to reject the null hypothesis, andinterpret the decision in the context of the original claim)

An epidemiologist claims the percentage of the seven classes of hospitalized COVID-19 patients you have constructed above is respectively 13%, 16%, 22%, 34%, 8%, 5%, and 2%. Atperform a chi-square goodness-of-fit test to test whether to reject, or fail to reject the epidemiologist's claim