Category: Statistics

Instructions  Part 1.1 | Part 1.2 | Part 1.3 | Part 1.4 | Part 1.5 | Part 2 |
Residents of Melbourne are complaining about the high cost of housing within a 41-kilometer radius (about 25 miles) of the Central Business District, saying that even apartments are too expensive to purchase. Residents are pressuring city government leaders to address the need for affordable housing. At the same time, real-estate investors are downplaying the residents’ concerns, saying that in fact, housing is affordable in Melbourne, and the real-estate investors are encouraging city-government leaders to focus their efforts on other issues of concern. Both the residents and real-estate investors presented their findings on apartment prices before the city government leaders. Your job is to determine the validity of each of their findings and to report your findings in the form of your own letter to city government officials. The summary of the data that the residents of Melbourne collected can be found in the Resident – data document [DOWNLOAD]. The summary of the data that real-estate investors collected can be found in the Real Estate Investors – Data [DOWNLOAD].
Set Up Google Sheets and a Google Doc for Part 2
Copy the Google Sheet containing the Property Prices – Part 2 Data (opens in new window) (information from 4296 apartments) and the pre-labeled tabs in which you will perform pertinent computations for the second part of the assignment. 
Rename your copy of the Google Sheet using your username, and share your copy of the spreadsheet with your professor. 
Copy the Google Slides – Part 2 (opens in new window – select use template) to use as a template for presenting your work for Part 2 of the assignment. 
Rename your copy of the Google Slides file using your username, and share your copy of the slides with your professor. 
Generate a Random Sample from the Data Set 
In TAB 4 of the Google Sheet – you will generate a simple random sample of 300 data values from the data set to be used for the remainder of this Final Assignment. Copy the original data set provided for you (TAB 1) and paste that entire data set into TAB 4. To do this, select inside the blank box in the top left corner of the spreadsheet. This will select all the cells. Then, right-select click to copy the data. Paste the data by selecting “Paste” in cell A1 in TAB 4. 
In cell I1 of TAB 4 label the column Random_Number. In cell I2, use the function =RANDBETWEEN(0,1000000) to generate a random number between zero and a million. Copy this fuction down column I, so that every row (2 through 4297) has a random number. Copy all of the random numbers in column I and then use Paste values only (CTRL+Shift+V) in column I, which will keep the random numbers from changing. Freeze the first row containing all the labels. Sort the entire sheet in TAB 4 based on the random numbers generated in column I. Use the first 300 rows as your random sample (2 through 301). You must delete rows 302 through 4297. 
Find and Interpret the 95% Interval for the Mean Apartment Price in Melbourne 
Copy the PRICE column from your random sample of apartment prices and paste it in Column A of TAB 5. Note that pertinent statistics will automatically be calculated for you, including the 95% confidence interval. 
As part of your presentation to city government officials (Google Slides – Part 2), state and interpret the 95% confidence interval for the mean apartment price in Melbourne. Additionally, make reference to any other statistics that you deem important in your own analysis of apartment prices. Review Chapter 8 of your text for reference on how to interpret the confidence interval. Make a recommendation to the city government leaders regarding the accuracy of the information that the residents provided in light of your confidence interval and data. 
Conduct a One-Sample Hypothesis Test of the Mean Individual Apartment Price in Melbourne 
According to the data that the real-estate investors collected, the mean individual apartment price within a 41-kilometer (about 25 miles) radius of the Central Business District of Melbourne is $453,993.94. You are going to use a hypothesis test to determine whether the true mean apartment price is higher than $453,993.94. Assume that apartment prices are normally distributed. 
i. The null and alternative hypotheses are as follows: 
H0: =$453,993.94 
HA: >$453,993.94 
Use your sample of n = 300 and your mean to conduct a hypothesis test using a 5% level of significance to determine if the mean apartment price is more than $453,993.94. Refer to example 9.16 from your text for additional guidance. 
As part of your presentation to city government officials (Google Slides – Part 2), explain the results of the one-sample hypothesis test conducted based on your data, and determine whether or not to reject the null hypothesis. Additionally, make reference to any other statistics that you deem important in your own analysis of apartment prices. In light of your analysis, make a recommendation to the city government leaders regarding the accuracy of the information that the real-estate investors provided. 
Conclusion 
Write a meaningful conclusion that summarizes your findings regarding both the residents and real-estate investors and make your own recommendation to the city government officials about apartment prices within 41-kilometers of the Central Business District of Melbourne. 
Ethical Considerations of Statistics 
In your Google Slides – Part 2 presentation, reflect on the tension between the pressure to manipulate data to support an existing desired outcome and employing proper statistical techniques to determine an outcome that is in line with ethical statistical practices and a Christian worldview in the context of the provided scenario regarding real-estate investors and city residents. See the Ethical Guidelines for Statistical Practice (opens in new window). For context about a Christian worldview in regard to work and communication of information, review this link from Truth, Honesty and Deception in the Workplace: Overview opens in new window). Pay special attention in this article to the introduction, conclusion, Truthtelling in the Bible (opens in new window), Why Truthtelling is Important (opens in new window), and There May Be Exceptions to Truthtelling in the Workplace (opens in new window). 
Submit a link to your shared presentation in Google Drive.
Resources
How to Share and Submit a Copy of Sheets and Slides [00:02:17]
Requirements
300-500 words in a new Google Slides File template (6 slides) in addition to the outlined deliverables in the slide template and instructions
Before you submit a file…
Check your document for spelling and grammatical errors.
Refer to your course syllabus (opens in new window) for details on grading criteria and the university’s late work policy.

Please do Applied Part (pdf file attached)
By using Class Data Set (SAV file attached).
-Send the answers as (word and pdf file)

Competency
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address research problems
Perform hypothesis testing to address an authentic problem
Overview
In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods.
Scenario
You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:
Are housing prices in your regional market lower than the national market average?
Is the square footage for homes in your region different than the average square footage for homes in the national market?
For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?
You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below.
Directions
Introduction
Region: Start by picking one region from the following list of regions:
West South Central, West North Central, East South Central, East North Central, Mid Atlantic
Purpose: What is the purpose of your analysis?
Sample: Define your sample. Take a random sample of 500 house sales for your region.
Describe what is included in your sample (i.e., states, region, years or months).
Questions and type of test: For your selected sample, define two hypothesis questions (see the Scenario above) and the appropriate type of test for each. Address the following for each hypothesis:
Describe the population parameter for the variable you are analyzing.
Describe your hypothesis in your own words.
Identify the hypothesis test you will use (1-Tail or 2-Tail).
Level of confidence: Discuss how you will use estimation and confidence intervals to help you solve the problem.
1-Tail Test
Hypothesis: Define your hypothesis.
Define the population parameter.
Write null (Ho) and alternative (Ha) hypotheses. Note: For means, define a hypothesis that is less than the population parameter.
Specify your significance level.
Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number])
Summarize your sample data, describing the center, spread, and shape in comparison to the national information (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Note: For shape, think about the distribution: skewed or symmetric.
Check the conditions.
Determine if the normal condition has been met.
Determine if there are any other conditions that you should check and whether they have been met. Note: Think about the central limit theorem and sampling methods.
Hypothesis test calculations: Complete hypothesis test calculations.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.
Calculate the probability (p value). Note: This calculation is done with the T.DIST function in Excel:
=T.DIST([test statistic], [degree of freedom], True) The degree of freedom is calculated by subtracting 1 from your sample size.
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
2-Tail Test
Hypotheses: Define your hypothesis.
Define the population parameter.
Write null and alternative hypotheses. Note: For means, define a hypothesis that is not equal to the population parameter.
State your significance level.
Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number])
Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Note: For shape, think about the distribution: skewed or symmetric.
Check the assumptions.
Determine if the normal condition has been met.
Determine if there are any other conditions that should be checked on and whether they have been met. Note: Think about the central limit theorem and sampling methods.
Hypothesis test calculations: Complete hypothesis test calculations.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.]
Determine the probability (p value). Note: This calculation is done with the TDIST.2T function in Excel:
=T.DIST.2T([test statistic], [degree of freedom]) The degree of freedom is calculated by subtracting 1 from your sample size.
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Compare the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
Comparison of the test results: Revisit Question 3 from the Scenario section: For your region, what is the range of values for the 95% confidence interval of square footage for homes?
Calculate and report the 95% confidence interval. Show or describe your method of calculation.
Final Conclusions
Summarize your findings: In one paragraph, summarize your findings in clear and concise plain language.
Discuss: Discuss whether you were surprised by the findings. Why or why not?

Which of the following is/are true about confidence intervals (choose one or more)
Group of answer choices
when we calculate a 95% confidence interval there is statistical significance
knowing the range of a parameter is more accurate than a point estimate
confidence interval of the mean = mean +/- a margin of error using a constant
confidence intervals are abbreviated CI
Flag question: Question 2
Question 21.25 pts
The constant used in calculating the 99% confidence interval in the proportion formula is:
Group of answer choices
1.645
1.96
3.54
2.576
Flag question: Question 3
Question 31.25 pts
If you use the Excel Data Analysis Tools to calculate the descriptive statistics and check the box “confidence level for mean” what do you do with this number to obtain the confidence interval? (choose one or more)
Group of answer choices
do nothing – this number is the conficence interval
use this value to calculate the lower and upper bound of the interval
add and subtract this value from the median
add and subtract this value to the mean
Flag question: Question 4
Question 41.25 pts
Why do we need confidence intervals? (choose one or more)
Group of answer choices
To express statistical uncertainty
To accurately state a range of a population parameter
To give insight about the magnitude of the effect
To tell us the chance (95%) of a particular outcome
Flag question: Question 5
Question 51.25 pts
When calculating  confidence intervals in this class the product of a constant times a margin of error is added and subtracted to what value to obtain the CI range?
Group of answer choices
median
standard deviation
alpha
mean
Flag question: Question 6
Question 61.25 pts
The average BMI for a sample of 10 preschoolers is 16.3, with a standard deviation of 1.4. What is the 90% confidence interval for the BMI of all preschoolers? (round to two decimal places)
Group of answer choices
(15.57, 17.03)
(15.29, 16.91)
(15.3, 17.3)
(15.49, 17.11)
Flag question: Question 7
Question 71.25 pts
When calculating the 99% confidence interval of the mean for a sample of 15 patients, what constant is used in the formula?
Group of answer choices
2.603
2.947
2.625
2.977
Flag question: Question 8
Question 81.25 pts
What affects the width of a confidence interval? (choose one or more)
Group of answer choices
Our desired confidence level.
Median of the sample
Sample size.
Variation within the population.
Flag question: Question 9
Question 91.25 pts
What is the constant used to calculate the 90% confidence interval of the mean when n=50?
Group of answer choices
2.576
1.645
1.96
Flag question: Question 10
Question 101.25 pts
If df=22, what constant do we use to calculate the 90% confidence interval of the mean?
Group of answer choices
1.321
1.717
1.714
1.323
Flag question: Question 11
Question 111.25 pts
If n=15, what constant do we use to calculate the 95% confidence interval of the mean?
Group of answer choices
1.762
2.132
2.145
1.753
Flag question: Question 12
Question 121.25 pts
As you increase your confidence level, what happens to the width of the confidence interval?
Group of answer choices
It stays the same.
It gets higher.
It gets narrower.
It gets wider.
Flag question: Question 13
Question 131.25 pts
When would you use the confidence interval formula for a proportion? (choose one or more)
Group of answer choices
You have summary information as a percentage or survey sample data
You do not know the standard deviation
Your sample size is under 30
To determine if the groups are significantly different
Flag question: Question 14
Question 141.25 pts
If in a sample of 355 adult males, we have a mean total cholesterol level of 185 mg, with s = 16. What is the 99% confidence interval for mean total cholesterol level of all males? 
Group of answer choices
(183.6, 186.4)
(183.34, 186.66)
(181.45, 188.37)
(182.81, 187.19)
Flag question: Question 15
Question 151.25 pts
Which of the following is/are true about the Excel function = CONFIDENCE.NORM
Group of answer choices
This is the appropriate function to use to calculate CI of a proportion
This is the appropriate function to use if the sample size is greater than 30
This function uses the normal distribution (table B.1)
This is the appropriate function to use if the sample size is less than 30
Flag question: Question 16
Question 161.25 pts
For a sample with df = 5, what is the t-score constant to calculate a confidence level of 99%? 
Group of answer choices
3.365
2.015
2.571
4.032
Flag question: Question 17
Question 171.25 pts
If n=20, what constant do we use to calculate the 99% confidence interval of the mean?
Group of answer choices
2.086
2.861
2.093
2.846
Flag question: Question 18
Question 181.25 pts
For a sample with df = 5, what is the t-score constant to calculate a confidence level of 95%? 
Group of answer choices
1.943
2.571
1.476
2.015
Flag question: Question 19
Question 191.25 pts
Researchers find that the 95% confidence interval for women’s systolic blood pressure is (126.67, 127.93). How do you interpret this finding?
Group of answer choices
We are 95% confident that the true mean for women’s systolic blood pressure is between 126.67 and 127.93.
All of the above.
There is a 95% chance that the true mean for women’s systolic blood pressure is between 126.67 and 127.93.
95% of the data values for women’s systolic blood pressure are between 126.67 and 127.93.
Flag question: Question 20
Question 201.25 pts
In a randomly selected sample of 500 Phoenix residents, 445 supported mandatory sick leave for food handlers. Legislators want to be very confident that voters will support this issue before drafting a bill. What is the 99% confidence interval for the percentage of Phoenix residents who support mandatory sick leave for food handlers?
Group of answer choices
(86.7%, 91.3%)
(86.26%, 91.74%)
(85.4%, 92.6%)
There is not enough information to determine CI

First, open this data file from within Jamovi. It contains data from a project on math anxiety and other variables. Here is the codebook for this data set (the codebook contains information about each variable and what it means, along with specific questions participants were asked and their response options). 
After opening the data set, locate the variables that relate to trait anxiety (STICSA – Trait). If you look at the codebook, these variables are Q9.1_1 through Q9.1_21, but they have two subscales: somatic (refers to the bodily experiences of anxiety) and cognitive (refers to mental experiences of anxiety). Find the questions that are on each subscale and compute a mean for each. There will be no reverse-coding.
Next:
1. Determine whether there is a correlation between these two subscales of the STICSA.
2. Produce a scatterplot.
3. Report the results in APA styLE 

Lab Assignment
The
highlight of this week’s lab is confidence intervals and the use of these
intervals in the health sciences. A short reading specifically relates
confidence intervals to health sciences. Then, you are asked to demonstrate
your knowledge of confidence intervals by practically applying them.
Step 1:
Use the two articles attached
step 2:
Consider using confidence intervals in health sciences with these articles as
inspiration and insights. (Articles attached)
Step 3:
Use the data collected below the Excel spreadsheet for the Week 5 Lab (heights
of 20 different people that you work. discuss
Using data collected above
the heights of 20 people, The participants of this study were selected using a
simple random sampling technique
·       Your
method of collecting the values that you are using in your study is simple random.
·        What are some faults with this type of data
collection?
·       What
other types of data collection could you have used, and how might this have
affected your study?
·       Write
a paragraph summarizing what you learned from the articles provided.  Consider the use of confidence intervals in
health sciences with these articles as inspiration and insights
Step 4:
Now, use the Week 6 Spreadsheet to help you calculate the following
questions/statements.
a)     Give
a point estimate (mean) for the average height of all people at your workplace.
Start by putting the 20 heights you are working with into the blue Data column
of the spreadsheet. What is your point estimate, and what does this mean? Example of exel
b)    
Find a 95% confidence interval for the
true mean height of all the people at your place of work. What is the interval?
[see screenshot below]
c)    
c)
Give a practical interpretation of the interval you found in part b, and
explain carefully what the output means. (For example, you might say, “I
am 95% confident that the true mean height of all of the people in my company
is between 64 and 68 inches”).
d) Post a screenshot of your work from
the t value Confidence Interval for µ from the Confidence Interval tab on the
Week 6 Excel spreadsheet attached , Example of excel
[O1] 
Step 5:
Now, change your confidence level to 99% for the same data, and post a
screenshot of this table, as well.
·      
Give a practical interpretation of the 99%
confidence interval (Write a complete sentence)
Example of Excel
Step 6:
Compare the margins of error from the two screenshots. Would the margin of
error be larger or smaller for the 99% CI? Explain your reasoning
·      
Would the margin of error be larger or
smaller for the 99% CI?
·      
Explain your reasoning. As the confidence
level increases, what happens to the Margin of Error?
Requirements
•           Length:2 page
•           1-inch margins
•           Double spaced
•           12-point Times New Roman font
•           APA format for in-text citations: Cite
the two articles.
•           Minimum of 2 scholarly sources
•           Chapter 2
-https://openstax.org/books/introductory-business-statistics/pages/1-1-definitions-of-statistics-probability-and-key-terms
[O1]

I have done the first 3 questions needed for the homework. I have 2 more left. 
Attached the screenshots for the questions. I need 14.21 and 14.35 be done please.
Exercise 14.3 is done and you will be able to see in the spreadsheet – you will need it for exercise 14.21.

You have a sample of 45 males, with an age range of 15-19, a mean height of 70.8 inches and a s of 1.5 inches.  What is the standard error of the mean?
Group of answer choices
1.5
1.34
0.2236
0.0333
Flag question: Question 2
Question 21.25 pts
Okunrintemi, V. et al (2019). Trends and costs associated with suboptimal physical activity among US women with cardiovascular disease. Jama Network Open 2(4):e191977
These data are based upon a nationally representative survey spanning 10 years.  Odds ratios were adjusted (a statistical term meaning to remove effects of different variables) but we still interpret them in the same way as you learned in the module.  
For each variable (i.e. age, income strata, race/ethnicity, health insurance…) the first group has an odds ratio of 1.  Why is that?  Why is there a group with on odds ratio of 1 within each variable?
Group of answer choices
No answer text provided.
The other groups are being compared to this group. The first group of each variable is the reference group.
The first group has no risk of disease based upon the exposure.
The first group (i.e. 18-39 year olds, high income, non-Hispanic white…) has the lowest risk of disease.
Flag question: Question 3
Question 31.25 pts
Which of the following are assumptions of a one-sample test?  (choose one or more)
Group of answer choices
normal distribution of data
ordinal or nominal scale of measurement
Interval or ratio scale of measurement
random sampling or selection
Flag question: Question 4
Question 41.25 pts
What is the Excel function for a one-sample z-test?
Group of answer choices
STANDARDIZE
ONE.SMPL 
T.TEST
Z.TEST
Flag question: Question 5
Question 51.25 pts
A ________ is a statistic that measures the magnitude of the relationship between variables.
Group of answer choices
t-test
Measure of effect
p-value
Confounder
Flag question: Question 6
Question 61.25 pts
In the United States, mothers who live in poverty generally have babies with lower birthweight than women who do not live in poverty. The average birthweight for women living in poverty is 2800 grams, with a standard deviation of 500. Recently, a local hospital introduced an innovative prenatal care program to reduce the number of low birthweight babies born in the hospital. In the first year, 35 mothers, all of whom live in poverty, participated in this program. Program evaluators want to determine if the birthweight for infants of women who participated in the program is greater than the average birthweight for women who live in poverty. They choose an α of 0.05. The following data is the birthweight in grams for the babies born to the mothers who participated in this program.
3550
2700
2425
2900
3100
3300
3075
2850
3150
2550
3500
2600
2300
3450
3100
3275
2600
3200
3250
2450
3350
3350
2725
3200
2600
3250
3400
2975
3425
2975
3450
3250
3125
2750
2600
Use the provided information and data to run a one-sample z-test in Excel.
05-8 Data_homework7-1.xlsxDownload 05-8 Data_homework7-1.xlsx
How would you write the null hypothesis?
Group of answer choices
H0: xbar  2800
Flag question: Question 7
Question 71.25 pts
The average birthweight for babies in the United States is 3,325 grams with σ = 525.  A researcher wishes to test whether or not a sample of 250 women in a rural community have a significantly different average birthweight than the national average at the α = 0.05 level. The mean birthweight for the sample of women in the rural community is 3400 grams.
What is the degrees of freedom for this study?
Group of answer choices
249
500
250
125
Flag question: Question 8
Question 81.25 pts
For which of the following scenarios would it be appropriate to use a one-sample z-test? (choose one or more)
Group of answer choices
Comparing the number of packs of cigarettes smoked per day by a sample of rural residents with the number of cigarettes smoked per day by all persons in the USA
Comparing the average weight of newborns in Hospital A to the average weight of newborns in Hospital B
Comparing political affiliation scores (ranging from 0-20) of ASU students against the political affiliation scores of all college students
Comparing the results of Likert scale patient satisfaction scores of patients at the Veterans Administration against the Likert scale patient satisfaction scores of the overall population of patients (non-VA patients)
Flag question: Question 9
Question 91.25 pts
The average birthweight for babies in the United States is 3,325 grams with σ = 525.  A researcher wishes to test whether or not a sample of 250 women in a rural community have a significantly different average birthweight than the national average at the α = 0.05 level. The mean birthweight for the sample of women in the rural community is 3400 grams. After calculating the test statistic from the  answer the following question:
True or False: this finding is statistically significant.
Group of answer choices
True
False
Flag question: Question 10
Question 101.25 pts
Okunrintemi, V. et al (2019). Trends and costs associated with suboptimal physical activity among US women with cardiovascular disease. Jama Network Open 2(4):e191977
These data are based upon a nationally representative survey spanning 10 years.  Odds ratios were adjusted (a statistical term meaning to remove effects of different variables) but we still interpret them in the same way as you learned in the module.  
Which of the following is the best interpretation of the odds ratio of 1.29 among low income strata women?
Group of answer choices
High income women with CVD have a 1.29 odds of engaging in suboptimal physical activity.
The odds of women with CVD engaging in suboptimal physical activity is 1.29 times greater in low income women as compared to high income women.
Low income women have a 129% greater chance of developing CVD.
There is no significant difference between high income women and low income women with CVD and their suboptimal physical activity.
Flag question: Question 11
Question 111.25 pts
In the United States, mothers who live in poverty generally have babies with lower birthweight than women who do not live in poverty. The average birthweight for women living in poverty is 2800 grams, with a standard deviation of 500. Recently, a local hospital introduced an innovative prenatal care program to reduce the number of low birthweight babies born in the hospital. In the first year, 35 mothers, all of whom live in poverty, participated in this program. Program evaluators want to determine if the birthweight for infants of women who participated in the program is greater than the average birthweight for women who live in poverty. They choose an α of 0.05. The following data is the birthweight in grams for the babies born to the mothers who participated in this program.
3550
2700
2425
2900
3100
3300
3075
2850
3150
2550
3500
2600
2300
3450
3100
3275
2600
3200
3250
2450
3350
3350
2725
3200
2600
3250
3400
2975
3425
2975
3450
3250
3125
2750
2600
Use the provided information and data to run a one-sample z-test in Excel.
05-8 Data_homework7-1.xlsxDownload 05-8 Data_homework7-1.xlsx
What is the p-value for the one-sample z-test?
Group of answer choices
0.0044
2.62
0.523
1.96
Flag question: Question 12
Question 121.25 pts
The purpose of the one-sample test is: (choose one or more)
Group of answer choices
To examine the difference between one sample and a population
Determine the probability that a sample and population are the same with respect to a particular variable
Compare a sample and population on a variable that is interval/ratio in measure
To compare a test statistic to alpha
Flag question: Question 13
Question 131.25 pts
In Excel functions, what does the output from the one-sample z-test represent?
Group of answer choices
The one-tailed probability value (p-value)
The significance level (alpha)
The obtained value
The critical value
Flag question: Question 14
Question 141.25 pts
Okunrintemi, V. et al (2019). Trends and costs associated with suboptimal physical activity among US women with cardiovascular disease. Jama Network Open 2(4):e191977
These data are based upon a nationally representative survey spanning 10 years.  Odds ratios were adjusted (a statistical term meaning to remove effects of different variables) but we still interpret them in the same way as you learned in the module.  
Which of the following odds ratios are significant at alpha = 0.05?  (select all that apply)
Group of answer choices
1.33 among Hispanic women
0.83 among women living in the West
1.07 among women living in the South
0.92 among Asian women
1.22 among African American women
Flag question: Question 15
Question 151.25 pts
Okunrintemi, V. et al (2019). Trends and costs associated with suboptimal physical activity among US women with cardiovascular disease. Jama Network Open 2(4):e191977
These data are based upon a nationally representative survey spanning 10 years.  Odds ratios were adjusted (a statistical term meaning to remove effects of different variables) but we still interpret them in the same way as you learned in the module.  
What is the best interpretation of the odds ratio of 0.81 among participants with some college under the variable education level?
Group of answer choices
There is no significant difference between in suboptimal physical activity among women with CVD based upon education.
High school educated women with CVD have a 0.81 odds of engaging in suboptimal physical activity.
The odds of women with CVD engaging in suboptimal physical activity is 0.81 among women with some college as compared to women without high school education. There is a protective effect of having some college education.
There is a 81% chance of women developing CVD if they have some college.
Flag question: Question 16
Question 161.25 pts
How do we interpret Cohen’s D of .61?
Group of answer choices
small effect
large effect
medium effect
Flag question: Question 17
Question 171.25 pts
In the United States, mothers who live in poverty generally have babies with lower birthweight than women who do not live in poverty. The average birthweight for women living in poverty is 2800 grams, with a standard deviation of 500. Recently, a local hospital introduced an innovative prenatal care program to reduce the number of low birthweight babies born in the hospital. In the first year, 35 mothers, all of whom live in poverty, participated in this program. Program evaluators want to determine if the birthweight for infants of women who participated in the program is greater than the average birthweight for women who live in poverty. They choose an α of 0.05. The following data is the birthweight in grams for the babies born to the mothers who participated in this program.
3550
2700
2425
2900
3100
3300
3075
2850
3150
2550
3500
2600
2300
3450
3100
3275
2600
3200
3250
2450
3350
3350
2725
3200
2600
3250
3400
2975
3425
2975
3450
3250
3125
2750
2600
Use the provided information and data to run a one-sample z-test in Excel.
05-8 Data_homework7-1.xlsxDownload 05-8 Data_homework7-1.xlsx
Use the provided information and data to run a one-sample z-test in Excel.
Based on this information the researcher should make the decision to ___________.
Group of answer choices
change the null hypothesis
reject the null hypothesis
change the alternate hypothesis
fail to reject the null hypothesis
Flag question: Question 18
Question 181.25 pts
In the United States, mothers who live in poverty generally have babies with lower birthweight than women who do not live in poverty. The average birthweight for women living in poverty is 2800 grams, with a standard deviation of 500. Recently, a local hospital introduced an innovative prenatal care program to reduce the number of low birthweight babies born in the hospital. In the first year, 35 mothers, all of whom live in poverty, participated in this program. Program evaluators want to determine if the birthweight for infants of women who participated in the program is greater than the average birthweight for women who live in poverty. They choose an α of 0.05. The following data is the birthweight in grams for the babies born to the mothers who participated in this program.
3550
2700
2425
2900
3100
3300
3075
2850
3150
2550
3500
2600
2300
3450
3100
3275
2600
3200
3250
2450
3350
3350
2725
3200
2600
3250
3400
2975
3425
2975
3450
3250
3125
2750
2600
Use the provided information and data to run a one-sample z-test in Excel.
05-8 Data_homework7-1.xlsxDownload 05-8 Data_homework7-1.xlsx
Use the provided information and data to run a one-sample z-test in Excel.
True or False, this finding is statistically significant (at the  = .05 level).
Group of answer choices
True
False
Flag question: Question 19
Question 191.25 pts
The average birthweight for babies in the United States is 3,325 grams with σ = 525.  A researcher wishes to test whether or not a sample of 250 women in a rural community have a significantly different average birthweight than the national average at the α = 0.05 level. The mean birthweight for the sample of women in the rural community is 3400 grams.
What is the test statistic?
Group of answer choices
-1.35
-0.37
0.14
2.26
Flag question: Question 20
Question 201.25 pts
In the United States, mothers who live in poverty generally have babies with lower birthweight than women who do not live in poverty. The average birthweight for women living in poverty is 2800 grams, with a standard deviation of 500. Recently, a local hospital introduced an innovative prenatal care program to reduce the number of low birthweight babies born in the hospital. In the first year, 35 mothers, all of whom live in poverty, participated in this program. Program evaluators want to determine if the birthweight for infants of women who participated in the program is greater than the average birthweight for women who live in poverty. They choose an α of 0.05. The following data is the birthweight in grams for the babies born to the mothers who participated in this program.
3550
2700
2425
2900
3100
3300
3075
2850
3150
2550
3500
2600
2300
3450
3100
3275
2600
3200
3250
2450
3350
3350
2725
3200
2600
3250
3400
2975
3425
2975
3450
3250
3125
2750
2600
Use the provided information and data to run a one-sample z-test in Excel.
05-8 Data_homework7-1.xlsxDownload 05-8 Data_homework7-1.xlsx
Use the provided information and data to run a one-sample z-test in Excel.
How would you write the alternative hypothesis?
Group of answer choices
Ha: xbar  2800
Ha: xbar = 2800

Answer the three questions and provide all of your work neatly on a piece of paper and send to me. This is required or I will not receive credit. The three problems are shown in the description.

The goal of this discussion board is to apply what you’ve learned to some data sets.
Pick two variables that are worth comparing. You should be able to picture two columns of data for each variables. For instance; if you wanted to compare two soccer teams, you could how many points the teams scored for several different seasons. Look below to see some examples!
Initial post:
1. Make an initial post that gives a brief description of the two variables you’ve chosen.
2. Make parallel box plots for the two columns of data (example below)
3.Calculate the mean, median, and standard deviation (and include them in your post)
Responses:
In your responses to classmates, check out their given information and answer the following:
– What’s the shape of each variable? (Is it symmetric or skewed?)
– What’s a good representation of the center of each variable? (Mean or median?)
-How do the two variables compare with regards to their spread?