Suppose we have a binomial experiment in which success is defined to be a particular quality or attribute that interests us.

(a)

• Suppose n = 36 and
• p = 0.39.

(For each answer, enter a number. Use 2 decimal places.)
n·p =
n·q =

Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)

_____, p̂ _____ be approximated by a normal random variable because _____ _____.

first blank

YesNo    

second blank

cancannot    

third blank

both n·p and n·q exceedn·p exceeds    n·p and n·q do not exceedn·q does not exceedn·p does not exceedn·q exceeds

fourth blank (Enter an exact number.)


What are the values of μ_p̂ and σ_p̂? (For each answer, enter a number. Use 3 decimal places.)
μ_p̂ = mu sub p hat =

σ_p̂ = sigma sub p hat =

(b)

Suppose

• n = 25 and
• p = 0.15.

Can we safely approximate p̂ by a normal distribution? Why or why not? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)

_____, p̂ _____ be approximated by a normal random variable because _____ _____.

first blank

YesNo    

second blank

cancannot    

third blank

both n·p and n·q exceedn·p exceeds    n·p and n·q do not exceedn·q does not exceedn·p does not exceedn·q exceeds

fourth blank (Enter an exact number.)

(c)

Suppose

• n = 46 and
• p = 0.33.

(For each answer, enter a number. Use 2 decimal places.)
n·p =
n·q =

Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)

_____, p̂ _____ be approximated by a normal random variable because _____ _____.

first blank

YesNo    

second blank

cancannot    

third blank

both n·p and n·q exceedn·p exceeds    n·p and n·q do not exceedn·q does not exceedn·p does not exceedn·q exceeds

fourth blank (Enter an exact number.)


What are the values of μ_p̂ and σ_p̂? (For each answer, enter a number. Use 3 decimal places.)
μ_p̂ = mu sub p hat =

σ_p̂ = sigma sub p hat =

The data set airquality is one of R’s included data sets. It shows daily measurements of ozone concentration (Ozone), solar radiation (Solar.R), wind speed (Wind), and temperature (Temp) for 5 summer months in 1977 in New York City. Some of the observations are missing and are recorded as NA, meaning not available. View an overall summary of the variables in airquality with the command

> summary(airquality) Ignore the summaries for Month and Day since those variables should be factors, not numeric variables, and their summaries are meaningless. Attach airquality to your workspace

> attach(airquality) and make boxplots of Ozone, Solar.R, Wind, and Temp. Comment on any noteworthy features.

Write a few sentences comparing bivariate correlation and bivariate regression. You need to discuss when it is appropriate to use each of these statistics.

Suppose Y is an random variable. If P(a<Y<2a)=0.16 and the median of Y is 5, what is a? Note: There may be more than one solution. Report all.

1. The Coefficient of Determination is *

a. the percent of variance in the dependent variable that can be explained by the independent variable

b. the ratio of the variance of Y to the variance of Y for a specific X

c. a measure of how strong the linear relationship is between the explanatory and response variables

2.

The null hypothesis for a regression model is state as *

a. beta_1=0: there is no relationship

b. beta_1 > 0: there is a positive relationship

c. rho=0: there is no relationship

d. rho < 1: there is a negative relationship

3.Choose the best interpretation of \beta_{0} *

a. the sample correlation between x and y

b. the change in y as x increases by 1 unit

c. the amount of uncertainty remaining after fitting the model

d. the value of y when all x's are zero

4.Linear regression analysis is used to assess the relationship between what two types of measurements? *

a. quantiative; quantitative

b. categorical; categorical

c. quantitative; categorical

1. Explain in words what a confidence interval means to someone who has never taken statistics.

2. There is concern that rural Minnesota is aging at a different rate than urban Minnesota. We want to test if the average age in rural Minnesota is different from the average age in urban Minnesota. Write out the null and alternative hypotheses.

3. At the 5% significance level, do you reject the null hypothesis? Why? Explain this to someone who has never taken statistics.

A random sample is drawn from a population with mean μ = 74 and standard deviation σ = 6.2. [You may find it useful to reference the z table.]

a. Is the sampling distribution of the sample mean with n = 18 and n = 47 normally distributed?

Yes, both the sample means will have a normal distribution.

No, both the sample means will not have a normal distribution.

No, only the sample mean with n = 18 will have a normal distribution.

No, only the sample mean with n = 47 will have a normal distribution.

b. Calculate the probability that the sample mean falls between 74 and 77 for n = 47. (Round intermediate calculations to at least 4 decimal places, “z” value to 2 decimal places, and final answer to 4 decimal places.)

So this week we learned about the four V's of Big data - Velocity, Volume, Veracity and Variety. As we know the velocity of data can vary so does it affect the other three V's? How are they affected? Also same if there are changes in other or one of the V then how are the rest affected?

This assignment is a series of short answer, multiple choice, and fill-in-the-blank questions based on the article, “The Effects of Hospital-Level Factors on Patients' Ratings of Physician Communication” (Al-Amin & Makaremet, 2016).

What statistical techniques were used for the results presented in Table 2?  Summarize the findings from this statistical analysis (20 points).

Statistical Technique:

Findings based on statistical technique:

            Overall model:

            Individual factors:

Assume that z is the test statistic. (Give your answers correct to two decimal places.)

(a) Calculate the value of z for Ho: μ = 10, σ = 2.8, n = 36, x = 11.4.

_________

(b) Calculate the value of z for Ho: μ = 120, σ = 26, n = 26, x = 125.9.

_________

(c) Calculate the value of z for Ho: μ = 18.2, σ = 4.4, n = 140, x = 18.88.

__________

(d) Calculate the value of z for Ho: μ = 81, σ = 13.5, n = 52, x = 78.6.

___________

Conduct a hypothesis test to determine if  companies with negative revenue change tend to be on the (500) market less time (and/or how much less time)?

The data is below. Please show all work in excel.

The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends on many factors, including the model year, mileage, and condition. To investigate the relationship between the car’s mileage and the sales price for Camrys, the following data show the mileage and sale price for 19 sales (PriceHub web site, February 24, 2012).

What are the issues with large significance values?

You discover an isolated population of island squirrels and collect 200 of them, finding leucism 12. Perform a hypothesis test for a difference in the proportions of leucism among this island population and the previously considered population. Report your conclusion at both the a=.01 and a=.05 level.

1.) Can you identify at least 6 holiday periods or special events that cause the spikes in the data?

a.) In each case give the week number, date, and what holiday or special event it represents

b.) Which holiday results in the maximum sales for this department and how much are the sales?

2.) Generate three linear models for this data. Each linear model should be generated from a pair of data points.

a.) For each linear model, find the equation of the line. Show your work. Write the equation in slope intercept form.

b.) For each linear model discuss the meaning of the slope and y-intercept. Also provide an analysis as to why you like or dislike that particular model

c.) Discuss the rationale behind the model that you believe best predicts future results.

3.) Predict and analyze sales for the next four weeks

a.) Using your most preferred linear model, predict sales for the next four weeks and show calculations

b.) Based on your preferred linear model, compute the percent rate of increase (y2-y1)/y1 for the next four weeks

4.) If you were a manager of this department store, what recommendation would you make to the person in charge of inventory?