Category: Statistics

Please try to make it as less confusing as possible. Do the problems in steps. For any multiple choice questions you can just simply put  1. B 2. C etc.
For the word problem I’ve uploaded some examplesof order you can write out the solved problems in that way so it’s confusing. The picture files has numbers in their orders as well. 

To access the pages and assignments listed, use Modules in the Left Navigation.
You will be working on the Semester Project throughout the term in parts as Project Part Assignments. Additional information can be found on the Semester Project Information page. You will get feedback from your instructor on the parts of the project in the Project Part as listed. Use that feedback to improve that portion of the project.
Project Part 3: Descriptive Statistics
1) Using the 35 values you created for Project Part 1, you will collect the following Descriptive Statistics using your TI-84 functions and explain what they tell you about your data.
If you did not collect the 35 values yet, review the Template and the Data Sets for Project Parts and the Semester Project page, and collect them now.
2) Click Stat > Line 1 Edit and enter your values into L1.
3) Stat > Calc > Line 1 1-Var Stats, into List enter L1 (use 2nd 1), and then enter to collect the following values:
Mean: use x¯¯¯
x
¯
Standard deviation: Sx (NOT σx)
5 Number Summary: (includes Min through Max at the bottom of the list)
Find the Mode(s) by clicking 2nd mode (to quit) then Stat > Line 2: SortA( enter 2nd 1 enter (for L1 if that is your list name), then 2nd 1 (to pull up L1) and click enter to view the entries in your list
Central Measures List your Mean, Median, and Mode(s) (if more than one Mode list all)
Provide at least 2 quality sentences describing which measure is best for your data and why.
Are these values close to each other, why or why not? 5 Number Summary
List the Minimum, Q1, Median, Q3, Maximum.
Find the IQR, and the Interquartile Range, and show your work. Using at least 2 quality sentences, describe what the 5 Number Summary and IQR tell you about your data. Do you have any outliers, if so what are they? Explain why you choose these as outliers. If you have no outliers explain how you know. Standard Deviation
List your Standard Deviation
Using at least 2 quality sentences, describe what the standard deviation tells you about the spread of your data. Is your data close together, or spread far apart? Explain in your own words. Do you have about 68% of your data within 1 standard deviation from the mean? Explain in your own words. When working on each part of the Semester Project the Best Practice is to type the information onto the appropriate slide of the Template, remove the directions, and then copy and paste your work and results into the text submission area of the assignment.
You may submit the project part as a text submission, Word Document, or PowerPoint Slide from the Template (only that slide!) Do not submit your work as an embedded image in one of those files. Images cannot be accepted for these assignments. (File Types allowed: .doc, .docx, ppt, .pptx)
Note: you will earn at most 10 points. If it is not submitted a 0 will be put in the grade book but it does not lower your grade.

To Prepare
Download and review the GSS Excel Data Set 
Download and review the GSS Codebook.
Choose 1 continuous variable and the first 50 participant responses.
Using Excel complete the following.
Create a grouped frequency distribution table using a continuous variable with the first 50 participant responses from the GSS data set. Use the variable assigned below.
The table should have two columns: the interval and frequency columns (you will make up this table on your own). There should not be more than ten intervals used. Place the table into the discussion board.
From the grouped frequency table, explain why you chose the intervals you did to divide the data.
Analyze how many frequencies you had for each of the intervals in your data.
Explain what your frequency table could tell us about the data collected for this variable.
Assigned variable:  ‘sei10’

Discussion 6 | Confidence Intervals
Number of replies: 3
REVIEW
Review the assigned reading to prepare for this discussion. 
For the Real Estate Evaluation Project, you have been working solely with a random sample of a data set of property prices. You found the mean price of homes, townhomes, and units of your sample. How confident can you be that the sample means are actually representative of the true mean of the property prices of all homes, townhomes, and units in the region represented by the data? In this discussion, you will use your data from Part 1 of the Real Estate Evaluation Project to explore the meaning of a confidence interval. In preparation for this discussion, it is imperative that you complete the assigned reading prior to posting, taking good notes and working through the examples in the text (Chapter 8, “Confidence Intervals”).
For our purposes, assume that the property prices of homes are normally distributed (this is a necessary condition for confidence intervals). The population standard deviation of the price of homes is known and is given by σ=$704,500.
Use your data set (TAB 2) from Part 1 of the Real Estate Evaluation Project to complete the table [DOWNLOAD]. For the sample size of n = 10, find the mean of the first 10 home prices from your random sample. For the sample size of n = 30, find the mean of the next 30 home prices from your random sample (not including the first ten home prices). For the sample size of n = 50, find the mean of the next 50 home prices from your random sample, which does not include any of the home prices used prior. For the sample size of n = 100, find the mean of the next 100 home prices from your random sample, which does not include any of the home prices used prior, if possible. Depending on how many homes were in your random sample, you may have to include some already-used property prices. Use technology, either Google sheets or another tool of your choice, to find the mean of the different samples.
RESPOND
Complete the table [DOWNLOAD], and share it with your peers as a part of your initial post. Embed your table directly into your discussion post on the discussion board.
Instructions for Embedding Pictures Into a Discussion Post [DOWNLOAD]
Interpret the confidence interval in the context of the problem for the n = 100 case. In Introduction to Statistics by Barbara Illowsky & Susan Dean, see the introduction of Chapter 8, as well as section 8.1, “A Single Population Mean Using the Normal Distribution” for guidance on the interpretation of a confidence interval.
How does sample size appear to affect the sample mean? How does sample size affect the 95% confidence interval, if at all.
Compare your 95% confidence interval for n = 100 with that of your peers. Additionally, comment on the role that sample size plays in statistics in general. What effect would the inclusion of sample size in a report that provides statistics have on an audience? Explain.
Requirements
Initial posts: 150-250 words
DISCUSS

12 statistics questions. Will have to send each question individually at a time. There will be a few parts to each question and some require work to be shown. You will have to been at your computer while calculating the problems however it should not take long. I will specify when questions need work shown and will need copies of it on paper for myself.

12 questions total. 2 will be given to you completely however, the other 10 must be answered in parts due to software.

Part 1
1. Open the Project Spreadsheet: Final Project (Part I) BUS 311 (2020) Tejeda.xlsx
2. Follow the instructions in the spreadsheet. 3. Upload your completed examination here before the deadline. Do not submit exams by email. Part 2:
I recommend that you create an Excel spreadsheet using either a desktop or laptop computer. I would strongly discourage you from attempting to create this on any of the following devices: Any phone, Any Tablet (with the exception of a Microsoft Surface), Chromebook or Linux-based system. I also recommend that you avoid Apple’s Numbers application as well as a Google doc spreadsheet. Create the following spreadsheet:
Column A: Observations. Use numeric or text to identify them. For example, “OBS 1” or simply “1”. Column B: The last 20 days of observed low temperatures in your home town. Column C: The last 20 days of observed low temperatures for Miami.
Guidance: These data are available through any weather service- simply request previous or historical data available when viewing the entire month.
Column D: Visit a traditional retailer with an online presence like Publix, Target, or Walmart and gather the name and price of 10 grocery items from a national maker.
Column E: Visit an online retailer such as Amazon and gather the name and price of the exact same 10 grocery items selected at brick and mortar retailer.
Guidance for Columns D&E: I suggest these be canned foods, bread, frozen foods- anything that is pre-processed and a national brand. The items should be exactly (or as close as possible) the same items just at two retailers. Avoid the deli, bakery, meat, and produce departments as these are internally prepared r seasonally available. Column F: Select 10 male friends and enter their ages.
Column G: Select 10 female friends and enter their ages.
Column H: Gather the GDP data of your country of Origin for the past 10 years.
Column I: Gather the GDP data of a country other than USA or your country of origin for the last 10 years.
Column J: Gather the GDP data of the USA for the last 10 years.
Guidance: GDP data is available at this web site; https://data.worldbank.org/indicator/ny.gdp.mktp.kd.zg
For the GDP website, simply enter the name of the country and use the cursor to gather the data. Note: some countries will not have a reporting convention. If your country or origin or your selected country does not have this information, simply select another location of interest.
Finally, document all the data collected beginning in column J. Clearly provide the detail that allows a person looking at your data set to understand all the variables and all the information that is present.
Once you are done with the Excel file, answer the following questions. Remember to provide evidence and screenshots of the analysis embedded in the results, as we discussed in class.
Final Project Questions
Is there a statistical difference in temperatures between your selected cities?
Is there a statistical difference in age between your male and female friends?
Is your age statistically different that your male friends?
Is your age statistically different that your female friends?
Are the prices of online retailers statistically less expensive than their traditional counterparts?
Are the prices of the online retailers statistically different than their traditional counterparts given that they are exactly the same products?
Is there a relationship between the GDP data from the two countries?
Does GDP of the USA have any bearing on the GDP of your country of origin of your first selected country?
Does GDP of the USA have any bearing on the GDP of your country of origin of your second selected country?
When you have completed your analyses and clearly labelled all components and results and stated those results, submit your final Excel spreadsheet
so you should send me two different things one for the first part and one for the second!!!

Activity 6: Compare House Prices of Two Areas in Miami
In this activity you are going to compare recently listed house prices in two areas in Greater
Miami by collecting data on your own and analyzing data using StatCrunch.
Part 1. Research question and data collection.
Consider two areas of your interest in the Greater Miami Area (Miami Date, Broward and Palm
Beach counties) by specifying city, or zip code, or neighborhood. For example, “Doral” and
“Kendall”.
1. Specify the areas below:
Area 1 (city/zip code/neightborhood): __________________________
Area 2 (city/zip code/neightborhood): __________________________
Go to www.realtor.com. Search for Area 1. Since the search results are sorted by new listing, we
may consider the first 10 search results as a random sample of recently listed houses in this
area. Fill in the table below with the listing prices of the first 10 results in thousand dollars. For
example, a house listed with $1,050,300 has a record of 1050.3 thousand dollars, so in the cell
you will record “1050.3”. Then repeat for Area 2. If you’d like, you may increase the sample size
by collaborating with other students. As what we have learned, the larger sample is always
better. If you worked with other students in collecting the data, identify them here.
Area1 (thousand dollars) Area 2 (thousand dollars)
Part 2. Use StatCrunch software to find a confidence interval. Answer the following questions.
1. Are the two samples of house prices independent or paired? ________________________
2. Based on the sample sizes, which statistic should we use, Z-statistic or T-statistic?
3. Choose a confidence level ___________. The commonly used levels include 90%, 95%, and
99%.
4. Let StatCrunch do the calculation.
STEP1: Load the data into StatCrunch by the following steps:
a. Copy the columns of “Area1 (thousand dollars)” and “Area 2 (thousand dollars)” in
above table including the header.
b. Launch StatCrunch website via MyLab.
c. Under “My data” choose “Paste data into a form”. Paste the data in the empty box,
check “Use first line as variable names”, and choose “Delimiter:” Tab. Select “Load
data”. You should see two columns of data with 10 rows of each in the worksheet.
STEP2: Find the confidence interval of the difference in mean house price.
a. From the worksheet, go to “Stat -> Z stats/T stats -> Two sample/Paired -> With data”.
Choose Z stats or T stats according to question 3, and choose two sample or paired
according to question 2. Notice that “two sample” in StatCrunch means independent
two sample procedure.
b. Under “sample 1 values in” select “Area1 (thousand dollars)”, and under “sample 2
values in” select “Area2 (thousand dollars)”. Select “Confidence interval”. Input the
level you chose in question 3. Click “Compute!”.
c. Fill in the following table with the output. Round the results in whole numbers.
____% confidence interval results:
μ1 : Mean of Area1 (thousand dollars)
μ2 : Mean of Area 2 (thousand dollars)
μ1 – μ2 : Difference between two means
(with pooled variances)
Difference Sample Diff. Std. Err. DF L. Limit U. Limit
μ1 – μ2
5. Interpret the confidence interval (L.Limit, U.Limit).
Part 3. Use StatCrunch software to perform hypothesis test. Answer the following questions.
6. Choose a significance level α=_______. The commonly used levels include 0.01, 0.05, and
0.10.
7. We want to test if there is a difference in the mean house prices in these two. Denote the
mean of Area 1 by μ1 and the mean of Area 2 by μ2. What are the hypotheses?
Ho:
Ha:
7. Perform the hypothesis test in StatCrunch.
a. Back to the worksheet, go to “Stat -> Z stats/T stats -> Two sample/Paired -> With
data”. Choose Z stats or T stats according to question 3, and choose two sample or
paired according to question 2.
b. Under sample 1 values in select “Area1 (thousand dollars)”, and under sample 2 values
in select “Area2 (thousand dollars)”. Select “Hypothesis test”. Enter the hypotheses
according to question 6. Then click “Compute!”.
c. Fill in the following table with the output. Round to at least 2 decimal places.
Hypothesis test results:
μ1 : Mean of Area1 (thousand dollars)
μ2 : Mean of Area 2 (thousand dollars)
μ1 – μ2 : Difference between two means
(with pooled variances)
Difference Sample Diff. Std. Err. DF T/Z-Stat P-value
μ1 – μ2
8. Based on the p-value from the output (no calculation is needed), at the significance level of
your choice in question 6, what is your decision, to reject Ho or not to reject Ho? Explain.
9. Write a complete conclusion of the hypothesis test.

You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.
Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.
Specifically you must address the following rubric criteria, using the Module Two Assignment Template:
Generate a Representative Sample of the Data
Select a region and generate a simple random sample of 30 from the data.
Report the mean, median, and standard deviation of the listing price and the square foot variables.
Analyze Your Sample
Discuss how the regional sample created is or is not reflective of the national market.
Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document.
Explain how you have made sure that the sample is random.
Explain your methods to get a truly random sample.
Generate Scatterplot
Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.
Observe patterns
Answer the following questions based on the scatterplot:
Define x and y. Which variable is useful for making predictions?
Is there an association between x and y? Describe the association you see in the scatter plot.
What do you see as the shape (linear or nonlinear)?
If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at?
Do you see any potential outliers in the scatterplot?
Why do you think the outliers appeared in the scatterplot you generated?
What do they represent?
You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics and/or square footage. The video may use different national statistics or solve for different square footage values.
What to Submit
Submit your completed Module Two Assignment Template as a Word document that includes your response, supporting charts, and Excel file.

About: In this assignment, you will be looking at statistical output for the ANOVA. The objective is to apply your understanding of how the ANOVA and hypothesis testing works to tell us whether we have a significant relationship between our variables. You will analyze provided data and write a report explaining the populations, variables, which one is the independent and dependent variable, and the results of the ANOVA hypothesis test.
Directions: Select ONE scenarios provided after the directions and complete the following report for your scenario.
Introduction (100 words minimum)
Explain what the independent and dependent variable is in your scenario
Provide the Null and Research hypothesis as based on the two variables provided
Methods (50 words minimum)
Descriptive Statistics: describe the observable differences between the groups (in other words compare their means)
State and briefly explain the f-statistic results (F-statistic and p-value in particular)
NOTE: YOU DO NOT HAVE TO CALCULATE ANY VALUES, ALL VALUES ARE PROVIDED IN THE STATISTICAL OUTPUT
3. Results (100 words minimum)
Interpret the results by explaining where there is a statistically significant relationship or not.
Make sure to state whether we accept or reject the null hypothesis.
Make sure to explain whether this means the two variables are statistically related or not.
4. Discussion (100 words minimum)
Provide some thoughts and considerations on why we obtained the results
Consider at least two additional variables that can explain the results
Clearly and fully explain how the additional variables can affect the results
Word Count: Your report should be about 350 words minimum! Include your word count at the end of your post.
Scenarios: Similar to our previous lab, here are some scenarios of various statistical outputs involving the ANOVA. Select ONE of the following to complete your assignment
ANOVA Lab Scenario 1: Days of Poor Mental Health by Religiousness
ANOVA Lab Scenario 2: Hours of TV by Level of Happiness
ANOVA Lab Scenario 3: Hours of Household Chores by Race
ANOVA Lab Scenario 1: Days of Poor Mental Health by Religiousness
About: In this scenario the researcher is interested in seeing if there is a difference in days of poor mental health between people of different religious levels
The groups that were examined were: Very religious, Moderately Religious, Slightly Religious, and Not Religious at All
Here are their results!
Statistical Output Begins
Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness
Level of Religiousness
N
Mean
Std. Deviation
Very religious
199
2.90
6.680
Moderately religious
585
3.82
7.208
Slightly religious
463
4.50
8.166
Not religious at all
643
5.74
8.400
F-statistic Output
Type of Variation
df
Mean Square
F-statistic
Sig. Level
Between Groups
3
589.560
9.645
p < .001 Within Groups 1886 61.128 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open ANOVA Lab Scenario 2: Hours of TV by Level of Happiness About: In this scenario the researcher is interested in seeing if there is a difference in hours of TV Watching per day between people of different happiness levels The groups that were examined were:Very Happy, Somewhat Happy, Not Too Happy Here are their results! Statistical Output Begins Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness Happiness Level N Mean Hours of TV Standard Deviation very happy 521 2.90 2.869 pretty happy 1358 3.48 3.504 not too happy 459 3.47 3.384 F-statistic Output Type of Variation df Mean Square F-statistic Sig. Level Between Groups 3 68.366 6.095 p = .002 Within Groups 1886 11.216 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open ANOVA Lab Scenario 3: Hours of Household Chores by Race About: In this scenario the researcher is interested in seeing if there is a difference in hours of household chores between people of different racial groups The groups that were examined were: White, Black, Other Here are their results! Statistical Output Begins Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness Happiness Level N Mean Hours of Household Chores Standard Deviation White 804 9.90 hours 10.095 Black 1849.66 15.488 Other 127 11.46 11.252 F-statistic Output Type of Variation df Mean Square F-statistic Sig. Level Between Groups 2 149.8 1.175 p = .309 Within Groups 1112 127.4 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open