Category: Statistics

I have uploaded the Rubric/Guidelines, Module Overview, Reading and Resources, and chapters from the textbook.

Open the Heart Rate Data Set in Excel
Using the classification of variables from the Unit 1 assignment as
qualitative, quantitative discrete, or quantitative continuous, match
each of the 3 variables to the most appropriate graph type. (For
example, qualitative data can best be displayed with a pie chart or bar
graph; continuous numerical data can best be displayed using a
histogram)
Use the graphing functions in Excel to create an appropriate graph
of the data for each variable. Remember to properly label and title your
graphs to identify what the graph is about clearly.

Please read the questions carefully. You will be required to use Microsoft Excel to complete the assignments. The grades will be based on your ability to calculate the correct answers, the methodology employed, and the interpretation of the results. 

You
are to write a short paper addressing one inaccurate statement that many people
might think is true (e.g., happier employees are more productive, vaccines
cause autism, boys are smarter than girls; please do not use these in your
paper) by means of finding and reporting 3-5 statistics from peer-reviewed journal
articles that disconfirm the claim you picked.

Assignment Deliverable
Complete the following on the Data tab of the Pastas R Us data file: The file is attached.
1) Calculate “Annual Sales” for each restaurant. Annual Sales is the result of multiplying a restaurant’s “SqFt.” by “Sales/SqFt.” The first value has been provided for you.
2) Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables. The formulas and the first results have been provided for you.
3) Create a boxplot (sometimes referred to as a box and whisker chart) for the “Annual Sales” variable.
4) Create a histogram for the “Sales/SqFt” variable.
Respond to the following questions on the Questions tab of the Pastas R Us data file:
1) Does the annual sales boxplot look symmetric?
2) Would you prefer the IQR instead of the standard deviation to describe the dispersion of the annual sales variable? If so, why?
3) Does the histogram show that the sales per square foot distribution is symmetric?
4) If the sales per square foot distribution is not symmetric, what is the skew?
5) If there are any outliers, which one(s)? What is the “SqFt” area of the outlier(s)?
6) Is the outlier(s) smaller or larger than the average restaurant in the data? What can you conclude from this observation?
7) What measure of central tendency may be more appropriate to describe “Sales/SqFt”? Why?

Follow instructions on files attached, cannot use same variables as the sample paper. Any questions let me know! Please use 1. Frequency table to include measures of central tendencies (mean, median, mode) and 2. Frequency table to include measures of variability ( interquartile range, variance, standard deviation, range) if possible, and use another one to seem like more research was done.

In this lesson’s assignment, you will complete a problem set in which you address levels of data and types of variables. Answers to the problems must be complete and written in formal narrative language. In addition, you will write a short essay related to data privacy. You will also explore the different types of graphs used to visualize data. Results from both Excel and SPSS should be copied and pasted into a Word document for submission.
Explain the concept of a random variable.  Explain what it means to say, “Variables must vary.”  Why is the concept of variables important for learning statistics?
List and define the four levels of measurement (using examples) discussed in this lesson’s introduction and resources. In your opinion, which one or more is the most appropriate for statistical analysis? Explain. 
Compare and contrast the characteristics of continuous and discrete variables. What is a common challenge of trying to calculate statistics using discrete variables?
Identify example variables from your professional and personal life at each level of measurement.  Explain why you selected the level you did for each, relying on this lesson’s resources for support.
Identify at least 4 (two of each) discrete and continuous variables from your own professional or personal life and explain why you selected the category you did for each, relying on this lesson’s resources for support.
Use the provided datasets for building one of each of the four chart types below.  For each chart, select a variable from the provided dataset with a measurement level that is best visualized by that chart type. Use APA style to label each chart. Each graph must contain a narrative description of what it represents and an interpretation of the image.  Use this narrative and the graph to tell a story with your data.
Pie chart
Bar chart
Scatterplot
Histogram
Length: 7 to 10 pages not including title page or reference page 
References: Include a minimum of 4 scholarly resources (This is only a minimum requirement. You should strive to include more than the minimum in all doctoral research). Be sure to reference Excel and SPSS as they are resources for this assignment, although not scholarly.

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.

Please create linear regression model to predict charges based on age,BMI,SEX,Smoker status, and region
Medical Cost Personal Datasets (kaggle.com)

In Unit 3 you were introduced to correlations and the relationship that exists between variables. We deal with and hear about correlations frequently in our everyday lives (Ex: The bus is running late, there must be a lot of traffic. My computer’s internet is running slow, there must be a lot of people on the Wi-Fi. Gas prices are going up, must be Bidens fault, etc.). The interesting part about these “correlations” is that they are all not necessarily true or related, we can sometimes make ourselves believe they are. For this discussion I want you to search the internet for a common correlation we see in society now a day. You can use social media, google, articles YouTube, etc., just make sure they are reliable and appropriate for class. Without doing further research explain how you think this correlation can be tested. What two variables would we have to measure in order to show a relationship for the topic you shared. Of course, we learned that correlation does not equal causation. So the goal of this exercise is to put that into practice and learn about what common correlations are out there that in fact could be misconceptions.