This is a written, statistical report, not simply a collection of different types of Excel output. It is not necessary to include the formulas you used or a copy of the dataset. When answering the questions, make sure to include any relevant statistics and/or the results of your calculations. Like any other written report, you will want to start with an introductory paragraph or problem statement and finish with a conclusion that summarizes the information presented.

1. Use descriptive statistics to summarize the data.

2. Develop a 95% confidence interval estimate of the mean age of unemployed individuals in Philadelphia.

3. Conduct a hypothesis test to determine whether the mean duration of unemployment in Philadelphia is greater than the national mean duration of 14.6 weeks. Use a .01 level of significance. What is your conclusion?

4. Is there a relationship between the age of an unemployed individual and the number of weeks of unemployment? Explain.

2. Blood pressure is independent of the blood group. We want to know, if the distributions attending to the blood group, in three referred samples attending to the type of blood pressure, they are distributed in the same way. To this end, a sample of 1500 subjects was collected and their blood group was determined and blood pressure was taken, classifying it as low, normal, and high. Obtaining the following results:

Use alfa at 0.05

You may need to use the appropriate appendix table or technology to answer this question.

A simple random sample with

n = 54

provided a sample mean of 23.5 and a sample standard deviation of 4.4. (Round your answers to one decimal place.)

(a)

Develop a 90% confidence interval for the population mean.

to

(b)

Develop a 95% confidence interval for the population mean.

to

(c)

Develop a 99% confidence interval for the population mean.

According to the sixth annual survey of employees of advertising agencies, carried out by the company Altschuler, Melvoin & Glasser, these employees can wait another excellent year for their compensation (Adveertising Age, December 1, 1997). To investigate if there is any difference in the annual compensation of artistic directors, suppose you select a random sample of 10 of them from each of four regions: West, South, North and Northeast, and what you want to do the research with 10% of error range.

In what ways do advertisers in magazines use sexual imagery to appeal to youth? One study classified each of 1509 full-page or larger ads as "not sexual" or "sexual," according to the amount and style of the dress of the male or female model in the ad. The ads were also classified according to the target readership of the magazine. Here is the two-way table of counts.

(a) Summarize the data numerically and graphically. (Compute the conditional distribution of model dress for each audience. Round your answers to three decimal places.)

(b) Perform the significance test that compares the model dress for the three categories of magazine readership. Summarize the results of your test and give your conclusion. (Use α = 0.01. Round your value for χ² to two decimal places, and round your P-value to four decimal places.)

Conclusion

Fail to reject the null hypothesis. There is significant evidence of an association between target audience and model dress.Reject the null hypothesis. There is significant evidence of an association between target audience and model dress.    Fail to reject the null hypothesis. There is not significant evidence of an association between target audience and model dress.Reject the null hypothesis. There is not significant evidence of an association between target audience and model dress.

(c) All of the ads were taken from the March, July, and November issues of six magazines in one year. Discuss this fact from the viewpoint of the validity of the significance test and the interpretation of the results.

This is not an SRS. This gives us no reason to believe our conclusions are suspect.This is an SRS. This gives us reason to believe our conclusions might be suspect.    This is not an SRS. This gives us reason to believe our conclusions might be suspect.This is an SRS. This gives us no reason to believe our conclusions are suspect.

6. The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Price in Dollars 135 138 163 168 192

Number of Bids    11    12   15 17 19

Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.

Step 3 of 6: Find the estimated value of y when x=163. Round your answer to three decimal places.

Step 4 of 6: Determine the value of the dependent variable yˆ at x=0.

b0, or b1, or x, or y.

Step 5 of 6: Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.

Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.

A certain academic program claims that their students graduate in less than 4 years on average. A random sample of 50 students is taken and the mean and standard deviation are found. The test statistic is calculated to be -1.69. Using a 5% significance level, the conclusion would be: a) there is sufficient sample evidence for the program’s claim to be considered correct. b) there is insufficient sample evidence for the program’s claim to be considered correct. c) there is insufficient sample evidence for the program’s claim to be considered incorrect. d) there is sufficient sample evidence for the program’s claim to be considered incorrect.

When traveling 40 mph (miles per hour), the distance that it takes Fred’s car to stop varies evenly between 120 and 155 feet. (This includes the reaction distance and the braking distance.) All of the questions are related to the stopping distance when Fred is traveling 40 mph.

a) Let S be the distance it takes for Fred’s car to stop at when traveling 40 mph. Find the distribution, parameter(s), and support of S.

b) What is the probability that it takes between 115 and 138 feet for the car to stop?

c) Find the expected distance it will take Fred to stop and the standard deviation of the stopping distance.

d) What values represent the middle 60% of Fred’s stopping distances?

e) Suppose a squirrel darts into the road as Fred is driving, and when Fred finally sees the squirrel and applies the brakes, the squirrel is 131 feet away. What is the probability that the squirrel survives its encounter with Fred (i.e. that Fred stops before he hits the squirrel)?

f) Fred knows that when it rains, it will take a minimum of 127 feet to stop. Fred is out driving while it is raining. If there is a stop sign that is 135 feet away, what is the probability that Fred stops in time?

Using plots and descriptive statistics is too simple for making any marketing decisions (T or F)

Median should always be preferred over mean because it is less sensitive to outliers (T or F)

If the data is largely skewed to right, median could be a better typical value than mean (T or F)

Discrete variable and continuous variable can be used at the same time for independent variables. (T or F)  

Regression analysis requires us to have at least one discrete independent variable.

USE SSPS FOR THIS APPLICATION EXERCISE!!!

A nurse at a health clinic hypothesizes that ear thermometers measure lower body temperature than oral thermometers. The nurse selects a sample of healthy staff members and took the temperature of each with both thermometers. The temperature data are below. What can the nurse conclude with α = 0.05?

a) What is the appropriate test statistic?
---Select--- na, z-test, One-Sample t-test, Independent-Samples t-test, Related-Samples t-test

b)
Condition 1:
---Select--- oral thermometer, body temperature, health clinic, staff members, ear thermometer
Condition 2:
---Select--- oral thermometer, body temperature, health clinic, staff members, ear thermometer

c) Compute the appropriate test statistic(s) to make a decision about H₀.
(Hint: Make sure to write down the null and alternative hypotheses to help solve the problem.)
p-value =   ; Decision:  ---Select--- Reject H0, Fail to reject H0

d) Using the SPSS results, compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and/or select "na" below.
d =   ;   ---Select--- na, trivial effect, small effect, medium effect, large effect
r² =   ;   ---Select--- na, trivial effect, small effect, medium effect, large effect

e) Make an interpretation based on the results. (select one)

-The ear thermometer measured significantly higher temperatures than the oral thermometer.

-The ear thermometer measured significantly lower temperatures than the oral thermometer.    

-There was no significant temperature difference between the ear and oral thermometer.

Let the independent random variables X1, X2, and X3 have binomial distributions with parameters n1=3, n2=5, n3=2 and the same probabilitiy of success p = 2/5.

Find P(X1=1-X3).

Find P(X1=X3).

Find P(X1+X2+X3>=1).

Find the expected value and variance for X1+X2+X3.

According to the Normal model ​N(0.052​,0.027) describing mutual fund returns in the 1st quarter of​ 2013, determine what percentage of this group of funds you would expect to have the following returns. Complete parts​ (a) through​ (d) below.

Explain the difference between a set that is well defined and one that is not. Give an example of a well-defined set. Name and describe your well-defined set using roster form and set-builder notation. Give an example of at least 1 subset. NO HANDWRITING PLEASE.

1. Listed below are attractiveness ratings made by participants in a speed dating session. Each attribute rating is the sum of the ratings of five attributes (sincerity, intelligence, fun, ambition, shared interests)

Use a 0.05 significance level to test the claim that there is a difference between female attractiveness ratings and male attractiveness rating by following the steps below:

1. (a) State the null and alternative hypotheses, indicate the significance level and the type of test (left-, right-, or two-tailed test).

2. (b) Calculate by hand the test statistic.

3. (c) Use the appropriate sheet in the Hypothesis Test and Confidence Interval template to complete all relevant computations (including the test statistic: compare with (b) to confirm your calculation is correct). Add a screenshot.

4. (d) Use the P-value obtained in (c) to explain whether or not the null hypothesis is rejected.

5. (e) Make a concluding statement.

6. (f) Comment on potential issues related to the validation of your result (Hint: the sub-

   jective nature of the measures)

4. Consider the relationship between the number of bids an item on eBay received and the item's selling price. The following is a sample of 5 items sold through an auction.

Price in Dollars 137 137 151 180 187

Number of Bids 11 12 15 16 17

Step 1 of 5: Calculate the sum of squared errors (SSE). Use the values b0= −1.8618 and b1= 0.1014 for the calculations. Round your answer to three decimal places.

Step 2 of 5: Calculate the estimated variance of errors, s2e. Round your answer to three decimal places.

Step 3 of 5: Calculate the estimated variance of slope, s2b1. Round your answer to three decimal places.

Step 4 of 5: Construct the 98% confidence interval for the slope. Round your answers to three decimal places.

Lower endpoint and Upper endpoint

Step 5 of 5: Construct the 90% confidence interval for the slope. Round your answers to three decimal places.

Lower endpoint and Upper endpoint