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?

The mean systolic blood pressure for people in the United States is reported to be 122 millimeters of mercury (mmHg) with a standard deviation of 22.8 millimeters of mercury. The wellness department of a large corporation is investigating if the mean systolic blood pressure is different from the national mean. A random sample of 200 employees in a company were selected and found to have an average systolic blood pressure of 124.7 mmHg.

a) What is the probability a random employees blood pressure is higher than 135 mmHg.

b) What is the probability that 200 randomly selected employees mean blood pressure is greater than 127 mmHg.

c) The wellness department is providing a new health program to their employees. Past studies have shown 9.9 % of their employees have high blood pressure. Find the probability that if the wellness department examines 200 randomly selected employees, less than 12 employees will have high systolic blood pressure. Do you think the new program significantly lowers the number of employees with a high blood pressure.

1. Develop a scatter plot with HRS1 (how many hours per week one works) as the dependent variable and age as the independent variable. Include the estimated regression equation and the coefficient of determination on your scatter plot.
2. Does there appear to be a relationship between these variables (HRS1 and age)? Briefly explain and justify your answer.
3. Calculate the slope (b₁) and intercept (b₀) coefficients and use them to develop an estimated regression equation that can be used to predict HRS1 given age. Conduct your analysis using Alpha (α ) of 0.05. Submit your Excel output or workings to receive full points. Hint: Use formulas and Excel, or Excel regression Tool (run a regression with HRS1 as dependent or y variable and age as independent or x variable).
4. Interpret the slope coefficient b₁ (the coefficient for the independent variable, age).
5. Use t and F to test for a significant relationship between HRS1 and age. Use α = 0.05 and make sure you know what hypotheses you are using to conduct the significance tests.
6. Calculate and interpret the coefficient of determination R². Based on this R², did the estimated regression equation provide a good fit? Briefly justify your answer. Hint: If you used Excel Regression Tool to answer part c, R² was reported with your output.
7. Use the estimated regression equation to predict the HRS1 for a 60 year old individual.

The weight of navel oranges of a domestic farm is normally distributed with a mean of 8.0oz and a standard deviation of 1.5oz. Suppose that you bought 10 oranges randomly sampled.

a) what are the mean of the sampling distribution and the standard error of the mean?

b) what is the probability that the sample mean is between 8.5 and 10.0 oz?

c) The probability is 90% that the sample mean will be between what two values symmetrically distributed around the population mean?