The percentage of cotton in material used to manufacture men's shirts follows. Construct a stem-and-leaf display for the data. Calculate the median and quartiles of these data. Choose the correct answer.

1. Write the regression equation.

2. Discuss the statistical significance of the model using the appropriate regression statistic at a 95% level of confidence.
3. Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.
4. Interpret the coefficient for the independent variable.
5. What percentage of the observed variation in income is explained by the model?
6. Predict the value of a person’s income with 3 children, using this regression model.

Study 1: Unemployment Rates in Areas Where Minimum Wages Are Higher in the Cities Than in Surrounding Suburbs City Unemployment Rates Suburb Unemployment Rates P1 P 1 = 0.069 P2 P 2 = 0.062 N1 N 1 = 52 cities N2 N 2 = 56 suburbs The Z(obtained) test statistic is 1.99. Using a significance level of .05, the Z(critical) is +1.645. Which of the following is the appropriate conclusion to your hypothesis test? The difference between the unemployment rates in the cities and the suburbs is statistically significant. The difference between the unemployment rates in the cities and the suburbs is not statistically significant. Suppose you conduct a second study and ask half as many people the same question. Suppose the proportions remain approximately the same. The new results are shown in the following table: Study 2: Unemployment Rates in Areas Where Minimum Wages Are Higher in the Cities Than in Surrounding Suburbs City Unemployment Rates Suburb Unemployment Rates P1 P 1 = 0.068 P2 P 2 = 0.061 N1 N 1 = 26 cities N2 N 2 = 28 suburbs When compared with the first study, you would expect the Z(obtained) test statistic to and the Z(critical) to . Without computing the test statistic for the second study, you your conclusion will be the same as your conclusion for the first study. Now that you have a sense of how changing the sample size affects the statistical significance of the statistical finding, what about whether the test is one-tailed or two-tailed? How does moving from a one-tailed test to a two-tailed test change the probability of rejecting the null hypothesis? The probability of rejecting the null hypothesis does not change. The probability of rejecting the null hypothesis decreases. The probability of rejecting the null hypothesis increases. How does changing the sample size, or changing from one-tailed to two, affect the importance of the statistical finding? Check all that apply. Sample size does not affect the importance of a statistical finding. Changing from two-tailed to one is more likely to produce a statistically significant finding, but that doesn't mean it will be more important. A small sample is more likely to result in an important statistical finding. A large sample is more likely to result in an important statistical finding.

In an effort to determine whether any correlation exists between the price of stocks of airlines, an analyst sampled six days of activity of the stock market. Using the following prices of Delta stock and Southwest stock, compute the coefficient of correlation. Stock prices have been rounded off to the nearest tenth for ease of computation.

Answer & show work

andswer and show work

answer n show work

Using a sample of 20 people, the testing agency found that 14 of them had better protection than that provided by the competitor. Do you have enough evidence to say/claom that your suncreen lotion provides better protection than the competitiors in a majority of cases? Use alpha = 0.01 to answer.

1. What are the apporiate hypotheses for situation?

2. the appropriate rejection rule is?

3. the calculated value of the appropriate test statistic is?

4. pretend that your test statistic is +4. what can you conclude?

5. WHat is the assumption of this test?

The Centers for Disease Control and Prevention Office on Smoking and Health (OSH) is the lead federal agency responsible for comprehensive tobacco prevention and control. OSH was established in 1965 to reduce the death and disease caused by tobacco use and exposure to secondhand smoke. One of the many responsibilities of the OSH is to collect data on tobacco use. The following data show the percentage of U.S. adults who were users of tobacco for a recent 11-year period

1. Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series. Do not round your interim computations and round your final answers to three decimal places. For subtractive or negative numbers use a minus sign. (Example: -300)
   
   y-intercept, b₀ =
   
   Slope, b₁ =
   
   MSE =
   
2. One of OSH’s goals is to cut the percentage of U.S. adults who were users of tobacco to 12% or less within nine years of the last year of these data. Does your regression model from part (b) suggest that OSH is on target to meet this goal?
   
   
   
   Use your model from part (b) to estimate the number of years that must pass after these data have been collected before OSH will achieve this goal. Round your answer to the nearest whole number. Yes or No
   
   years=

For Exercises 49–52, identify the independent and dependent variables for each study.

49.A study was conducted to determine if crocodiles raised in captivity (i.e., in a zoo) grew faster than crocodiles living in the wild. Identify the explanatory variable and the outcome variable.

50.People who walk at least 3 miles a day are randomly selected, and their blood triglyceride levels are measured in order to determine if the number of miles that they walk has any influence on these levels.

51.In an article in the British Journal of Nutrition, two types of mice were randomly selected. One group received a thyme supplement for a specific time, while another group was used as a control group and received no supplements. The brains of the mice were then analyzed, and it was found that the brains of the group of mice that received the thyme supplements had antioxidant levels similar to those of younger mice. It was concluded that the thyme supplement increased the antioxidants in the brains of the mice.

52.A study was conducted to determine if workers who had a flexible work schedule had greater job satisfaction than those workers who worked a regular nine-to-five work schedule. Independent variable—type of work schedule.

An apartment complex surveyed its tenants and asked a variety of questions about their living arrangements. One question asked for the renter’s marital status using categorical responses of single, married, divorced, and widowed. Another question asked for the renter’s pet ownership with the categorical Dog, Cat, both (cat and dog) and none (neither cat nor dog).

1. Methods: Explicitly state and conduct the appropriate hypothesis test to determine if there is any relationship between pet ownership and marital status? (All steps should be included)
2. Discussion: Interpret the statistical decision you arrived at in terms that would be useful for apartment policies and procedures. This section should also include suggestions for further research and/or discussion of additional variables that may provide more precise results.

   Marital Status	Pets
   Divorced	none
   Widowed	both
   Single	cat
   Divorced	dog
   Single	Dog
   Married	cat
   Single	both
   Married	cat
   Single	cat
   Widowed	none
   Divorced	cat
   Married	Dog
   Single	none
   Married	none
   Divorced	Dog
   Married	cat
   Widowed	both
   Married	none
   Married	none
   Widowed	cat
   Divorced	both
   Single	cat
   Single	Dog
   Single	Dog
   Married	none
   Married	Dog
   Single	Dog
   Married	cat
   Single	cat
   Single	both
   Married	cat
   Divorced	Dog
   Divorced	none
   Married	both
   Married	both
   Widowed	dog
   Married	both
   Married	cat
   Single	cat
   Widowed	none
   Divorced	cat
   Married	Dog
   Divorced	both
   Single	cat
   Single	Dog

a. Write the reqression equation.

2. Discuss the statistical significance of the model using the appropriate regression statistic at a 95% level of confidence.
3. Discuss the statistical significance of the coefficient for the independent variable using the appropriate regression statistic at a 95% level of confidence.
4. Interpret the coefficient for the independent variable.
5. What percentage of the observed variation in income is explained by the model?
6. Predict the value of a person’s income who works 50 hours a week, using this regression model.

A survey was conducted to determine whether differences in health care expenditure exist between men and women. Dataset contains total amounts spent on health care. a. Formulate the hypothesis that can be used to determine whether the sample data support the hypothesis that men and women spend different amounts on health care. b. What is the point estimate of the difference between the means for the two populations? c. Using the p-value and critical value approaches, what is your conclusion at α = 0.05? Make sure to report the p-value and critical values you used.

The building specifications in a certain city require that the sewer pipe used in residential areas have a mean breaking strength of more than 2500 pounds per lineal foot. A manufacturer who would like to supply the city with sewer pipe has submitted a bid and provided the following information: An independent contractor randomly selected seven sections of the manufacturer’s pipe and tested each for breaking strength. The results (pounds per lineal foot) are as follows: 2610, 2750, 2420, 2510, 2540, 2490, and 2680.

1. What type of test should be conducted?

Dependent t test

Independent t test

One sample t test

2. State the null hypothesis in equation format.

3. State the alternative hypothesis in equation format.

4. What is the calculated t-value (to 3 significant digits)?

5. What is the critical t-value (to 3 significant digits)? Use alpha = 0.05.

6. Is the null hypothesis accepted or rejected? Use alpha = 0.05.

7. Is there sufficient evidence to conclude that there is a difference between the mean rate of increase of total phosphorus of the control algal and the water hyacinth? Use alpha = 0.05. Explain in one sentence.

On each turn, bonnie is tossing a fair coin and Clyde is rolling a fair die. They stop once Clyde rolls an odd number for the first time. Let X be the number of "Heads" that Bonnie's coin showed.

a) Compute E[X]

b) Compute var(X)

Please answer these questions using SPSS. Thank you

Note: For all assignments, you must show the requested output from SPSS.

Example. Determine the descriptive statistics for three quantitative variables. Which variable has the highest mean? The most variability?

Answer: Output should include 3 boxes of descriptive statistics, one for each variable. There should also be one page that gives the answer to the other two questions.

The following sample data are used. We are interested in the descriptive statistics from these variables: sleep duration of undergrads, the number of NBA wins and the number of words in a résumé). Assume that they are all samples from populations. Use the instructions from the first two recitation worksheets to help you.

¹ This is a survey of the amount of sleep for one night for 40 undergraduates.

² These are the numbers of wins for the 30 National Basketball Association teams for the 2014-2015 NBA season.

³ A large university offers training on résumé construction. This lists the number of words in each of 23 résumés.

Note: Here are the 5% Trimmed Means for these variables. This will help you make sure you’ve input the data correctly: Amount of sleep: 419.94 minutes. Wins: 42.69. Words: 257.72.

1. Input the data the way you learned in recitation. You can input all of the data (3 data sets) at the same time, but you must run the analysis of each variable individually, otherwise SPSS won’t read it correctly, because the sample sizes are different. [Compare your descriptive statistics with the means and standard deviations on your graphs; this will help you make sure100405405 your numbers are correct.] In addition, I want you to add another variable next to the words variable which will divide the variable “Words” categorically. I want you to call this variable “wordscat.” (Note: this is the variable name. The variable labelcan be more descriptive, e.g., Words by Category). Create this variable using the Transform procedure you used in lab. Remember that you will have to give this variable Value Labels in the Variable View.

The scores should be divided into categories like this:

Low: 100-200              Moderate: 201-300           High: 301-400

2. For all the quantitative variables (wordscat is categorical) find descriptive statistics (using Explore). Print out “Descriptives” and Stemplot. Remember to do this for each variable individually. If you try to do them at the same time your answers will be incorrect.

3. For all the quantitative variables (wordscat is categorical) create and print out frequency distributions and histograms (using Frequencies). Remember to do this for each variable individually. If you try to do them at the same time your answers will be incorrect. Note: When doing the histogram, if you check the box “Show Normal Curve” this does not mean your variable is normal. It just shows what normal would look like and you can compare the shape of your variable to what is normal.

4. For the categorical variable (wordscat) create and print out a bar chart. Make sure the variable is categorical on your chart and remember to label the chart.

5. Create a variable (call it “sleeptwo”) that multiplies each student’s amount of sleep by 2 (do this by using Transform > Compute like in Lab 2, but instead of adding, we are multiplying by 2. Use this sign * for multiplication). Repeat steps 2 and 3 above for the new variable.

On your separate page please answer the following questions (worth 8 points):

6. Calculate the SS for each of the three main quantitative variables using the variance you obtained in SPSS (this should be on a sheet separate from the SPSS output). Note: Remember the relationship between variance and SS to help you do this.

7. Write 1-2 sentences (on your separate page) for each of the three main quantitative variables including the following: values of the mean, median, standard deviation and approximate shape of the distribution (look at the histogram). The shape may not be obvious; this is ok. Just do your best to describe what you think is going on with the data (e.g., mention whether you think there is skew, are there are any outliers, is it bimodal?).

8. Answer the following questions:
   1. What happened to the mean and standard deviation of sleeptwo compared to the original mean and standard deviation of that variable?
   2. What happened to the shape of the distribution of the sleep variable after multiplying by two (compared to the original variable)? What is the explanation for this?