Category: Statistics

Directions

Using the “North Valley Real Estate” Excel Dataset located in the “Files” Section of the course (Left-hand Side Menu Bar). The Final Research Project for the course, and all supporting assignments to the project, will be executed using the “North Valley Real Estate” dataset.

Please make sure that your paper conforms to APA style requirements, 7th edition.

General Guidelines for a Successful Capstone Term Project Report include the following:

1. Provide a general introduction, background, and purpose of the paper, with your thesis resting on the idea of using statistical analysis to achieve better business decision and increase profitability and business activities. Also, include a discussion of the real estate industry and the impacts that influence the health, viability, and success of the real estate marketplace; particularly in the Northeastern region of the U.S.
2. State why the dependent variable has been chosen for analysis. Then make a general statement about the model you will be employing, for example:

The dependent variable _______ is determined by variables ________, ________, ________, and __________.

1. Identify the primary independent variable and defend why it is important by stating:

The most important independent variable in this analysis is ________ because _________.

In your paragraphs, cite and discuss the research sources/references that support the thesis, i.e., the model you have chosen.

1. Write the general form of the regression model (less intercept and coefficients), with the variables named appropriately so the reader can identify each variable at a glance:

Dep_Var = Ind_Var_1 + Ind_Var_2 + Ind_Var_3

• For instance, a typical model would be written:

Price_of_Home = Square_Footage + Number_Bedrooms + Lot_Size.

• Price_of_Home: brief definition of dependent variable
• Square_Footage: brief definition of first/primary independent variable
• Number_Bedrooms: brief definition of second independent variable
• Lot_Size: brief definition of third independent variable

1. Define and defend all variables, including the dependent variable, in a single paragraph for each variable. Also, state the expectations for each independent variable. These paragraphs should be in numerical order, i.e., dependent variable, X1, then X2, etc. In each paragraph, the following should be addressed:

• How is the variable defined in the data source?
• Which unit of measurement is used?
• For the independent variables: why do the independent variables determine the dependent variable?
• What sign is expected for the independent variable’s coefficient, positive or negative? Why?

1. Data Description: Describe the data and identify the data sources. From which general sources and from which specific tables are the data taken? Which year or years were the data collected. Are there any data limitations?
2. Presentation and Interpretation of Results. Write the regression (prediction) equation:

Dep_Var = Intercept + c1 * Ind_Var_1 + c2 * Ind_Var_2 + c3 * Ind_Var_3

1. Identify and interpret the adjusted R2 (one paragraph). Define adjusted R2, what does the value of the adjusted R2 reveal about the model? If the adjusted R2 is low, how has the choice of independent variables created this result?
2. Identify and interpret the F-test (one paragraph). Using the p-value approach, is the null hypothesis for the F-test rejected or not rejected? Why or why not? Interpret the implications of these findings for the model.
3. Identify and interpret the t-tests for each of the coefficients (one separate paragraph for each variable, in numerical order): Are the signs of the coefficients as expected? If not, why not? For each of the coefficients, interpret the numerical value. Using the p-value approach, is the null hypothesis for the t-test rejected or not rejected for each coefficient? Why or why not? Interpret the implications of these findings for the variable. Identify the variable with the greatest significance.
4. Analyze multicollinearity of the independent variables (one paragraph); Generate the correlation matrix. Define multicollinearity. Are any of the independent variables highly correlated with each other? If so, identify the variables and explain why they are correlated. State the implications of multicollinearity (if found) for the model you have created for this analysis.
5. Other (not required): If any additional techniques for improving results are employed, discuss these at the end of the paper. As for grading, the inclusion of additional statistical methods will be rewarded appropriately.
6. Reference Page: Use the proper format to list the works cited and place the entire page in APA format 7th edition. Include at least 10 references from across the spectrum of possible reference sources (books, magazines, journals, periodicals, newspapers, videos, etc.)

ive inserted a working copy of my project so please add on to that and send it back please. please review the instructions and attachments for the project.

PLEASE RESPOND TO EACH (130 words each responses) PLEASE MAKE IT SOUND VERY CASUAL

1) Hello Everyone,

The median better describes the days between grocery orders. To find the mean, I added all 40 values together and got the sum of 486. Then I proceeded to divide the sum of the values by the total number of values (486/40), which gave a mean of 12.15 days. To find the median, I arranged the numbers from smallest to largest. Since there are 40 numbers (even amount), I found the middle two values, which were the 20th and 21st numbers. Both of those numbers were 8, so the median is 8 days. The data included several large values like 28, 29, and many 30s. These higher numbers raise the means, making it larger than most of the typical values. Because of this right-skewed shape, the median gives a better idea of what is normal for customers.

The level of measurements is ratio because days have a true zero and can be compared using multiplication. For example, 10 days is twice as 5 days, a value of zero would mean a customer placed orders on the same day. This shows the data have equal interval and meaningful differences between numbers.

Instacart could use this information by sending reminders around 7 or 8 to encourage customers to reorder. This could increase sales and improve planning. The company could also offer small discounts before the average reorder time to motivate customers. In addition, knowing typical ordering patterns helps with staffing, inventory control, and delivery scheduling. This allows the company to make smarter business decisions based on customer behavior.

2)Good morning class,

In reviewing the data from Problem 28, which shows the number of days between grocery orders at Instacart, I began by calculating the mean and median. The mean number of days between orders is approximately 12.63, while the median is 8.5. This noticeable difference between the two values prompted me to examine the data distribution in greater detail. After organizing the data into a histogram, it became clear that the distribution is right-skewed, with most values concentrated at the lower end and a long tail extending toward higher values. Many customers placed orders around 5 to 8 days apart, but there are multiple high outliers, such as 28, 29, and several 30s, that extend the range and pull the mean upward. This skewness is important because it indicates that the mean is distorted by extreme values, whereas the median remains stable and better reflects the typical ordering behavior (Sullivan, 2025). For that reason, the median is the more appropriate measure of central tendency for this data.

The level of measurement for this data is ratio, since the values represent countable quantities, have equal intervals, and contain a meaningful zero, indicating the possibility of no time between orders. Instacart could use these insights strategically. If the majority of customers reorder between 5 and 9 days, the company might time promotional emails or app notifications around day 6 to encourage reordering. On the other hand, recognizing that a smaller group places monthly orders, as seen in the cluster of 28-to-30-day intervals, could lead to targeted reminders or subscription-based offers tailored to those users habits.

Overall, analyzing both the numerical and visual elements of the data supported my conclusion that the median provides a clearer picture of customer behavior. The histogram shape, especially its skewness, played a role in justifying that choice.

Reference:

Sullivan, M., III. (2025). Statistics: Informed decisions using data (7th ed.). Pearson

THIS IS THE ASSIGNMENT PROMPT

Complete problem 28, “Online Shopping” in Ch. 3 of your textbook.

The data in the problem represents the number of days between grocery orders at the online delivery company Instacart. Determine the shape of the distribution of days between orders by drawing a frequency histogram. Find the mean and median days between orders.

Respond to the following in a minimum of 175 words:

• Which measure of central tendency better describes the days between orders?
• What level of measurement is this data?
• How would Instacart use this information for its marketing efforts?
• Include your justification for your thinking.

PLEASE SITE and GET INFORMATION HERE

Sullivan, M., III. (2025). Statistics: Informed decisions using data (7th ed.). Pearson.

MEAN DIFFERENCES ASSIGNMENT You will take part in several data analysis assignments in which you will develop a report using tables and figures from the IBM SPSS output file of your results. Using the resources and readings provided, you will interpret these results, test the hypotheses, and write up these interpretations. This assignment has three parts: Complete the Additional Exercises on page 261 (Chapter 17) Business Data file: staffsurvey.sav. See Classroom for file. See Appendix for details of the data file. 1. Follow the procedures in the section on independent-samples t-tests to compare the mean staff satisfaction scores (totsatis) for permanent and casual staff (employstatus). Is there a significant difference in mean satisfaction scores? Health Data file: sleep.sav. See Classroom for file. See Appendix for details of the data file. 1. Follow the procedures in the section on independent-samples t-tests to compare the mean sleepiness ratings (Sleepiness and Associated Sensations Scale total score: totSAS) for males and females (gender). Is there a significant difference in mean sleepiness scores? Complete the Additional Exercises on page 280 (Chapter 18) Business Data file: staffsurvey.sav. See Classroom for file. See Appendix for details of the data file. 1. Conduct a one-way ANOVA with post-hoc tests (if appropriate) to compare staff satisfaction scores (totsatis) across each of the length of service categories (servicegp3). Health Data file: sleep.sav. See Classroom for file. See Appendix for details of the data file. 1. Conduct a one-way ANOVA with post-hoc tests (if appropriate) to compare the mean sleepiness ratings (Sleepiness and Associated Sensations Scale total score: totSAS) for the three age groups defined by the variable agegp3 (37 or under, 3850, 51+). Complete the Additional Exercises on page 289 (Chapter 19) Business Data file: staffsurvey.sav. See Appendix for details of the data file. 1. Conduct a two-way ANOVA with post-hoc tests (if appropriate) to compare staff satisfaction scores (totsatis) across each of the length of service categories (servicegp3) for permanent and casual staff (employstatus). Health Data file: sleep.sav. See Appendix for details of the data file. 1. Conduct a two-way ANOVA with post-hoc tests (if appropriate) to compare male and female (gender) mean sleepiness ratings (Sleepiness and Associated Sensations Scale total score: totSAS) for the three age groups defined by the variable agegp3 (37 or under, 3850, 51+). General Instructions As doctoral students, your assignments are expected to follow the principles of high-quality scientific standards and promote knowledge and understanding in the field of criminal justice. You should apply a rigorous and critical assessment of a body of theory and empirical research, articulating what is known about the phenomenon and ways to advance research about the topic under review. Research syntheses should identify significant variables, a systematic and reproducible search strategy, and a clear framework for studies included in the larger analysis. Manuscripts may be written in first person (I). All manuscripts should be clearly and concisely written, with technical material set off. Please do not use jargon, slang, idioms, colloquialisms, or bureaucratese. Use acronyms sparingly and spell them out the first time you use them. Please do not construct acronyms from phrases you repeat frequently in the text. General Instructions As doctoral students, your assignments are expected to follow the principles of high-quality scientific standards and promote knowledge and understanding in the field of criminal justice. You should apply a rigorous and critical assessment of a body of theory and empirical research, articulating what is known about the phenomenon and ways to advance research about the topic under review. Research syntheses should identify significant variables, a systematic and reproducible search strategy, and a clear framework for studies included in the larger analysis. Manuscripts may be written in first person (I). All manuscripts should be clearly and concisely written, with technical material set off. Please do not use jargon, slang, idioms, colloquialisms, or bureaucratese. Use acronyms sparingly and spell them out the first time you use them. Please do not construct acronyms from phrases you repeat frequently in the text. Structure of Assignment Paper For purposes of this assignment, there is no layout structure required as far as the setup of this paper, with one exception. I would appreciate it if you used separate headers for questions. Sub- headers are also allowed but not required. Questions should strive to be no less than 100 words each with no maximum limit. There is no overall page limit. I expect all papers to be in the latest APA edition, properly cited, and tables attached in the correct format. Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.

I only need the task:

A3.The Confounding Test (10 marks)

A4. Multicollinearity Check (15 marks)

techniques of change management, which is why we are continuing to explore SPSS.

General Requirements:

Use the following information to ensure successful completion of the assignment:

• Doctoral learners are required to use APA style for their writing assignments. The APA Style Guide is located in the Student Success Center.
• You are not required to submit this assignment to LopesWrite.

Directions:

1. View “Simple Linear Regression Using SPSS” located at https://www.youtube.com/watch?v=6xcQYmPDqXs
2. Open SPSS and complete the following:
3. Obtain an output with a simple linear regression and a scatterplot graph (as in the tutorial, with the values as seen below); highlight the model summary and coefficients table, and upload it to the digital classroom.

Caffeine Dose IQ Score

50 100

60 102

80 107

90 105

110 112

150 108

150 103

160 109

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200 112

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220 121

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250 130

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300 135