Professional Development Presentation: Descriptive Statistics

Professional Development Presentation: Descriptive Statistics

Professional Development Presentation: Descriptive Statistics

Understanding measurement principles and the characteristics of assessments helps to minimize bias in individual teacher assessment practices. The ability to explain descriptive statistics encourages deeper understanding of how data is derived to aid decision-making within the classroom setting. These skills will support collaboration with colleagues and families in making decisions about students with disabilities to help inform future instructional practices.

Create a digital presentation, to be used for professional development, which creatively and accurately explains the dimensions of descriptive statistics. Your presentation should be 10-15 slides, including a title slide, reference slide, and presenter’s notes.

Within your presentation, explain each of the following:

Reliability

Validity

Bell curve

Mean

Standard deviation

Standard scores

Scaled scores

T-Scores

Percentiles

Conclude your presentation by describing how this knowledge relates to data literacy and why it is important for teachers to understand it when making educational decisions and differentiated instruction for individual students, including those with disabilities.

Your presentation should include visual depictions of sample statistics through graphs, tables, scatter plots, advanced organizers, etc. when it is helpful for explaining the required element.

The digital presentation should include graphics that are relevant to the content, visually appealing, and use space appropriately.

Support your findings with a minimum of two scholarly resources.

Descriptive Statistics

Number of accidents caused by red-runners in the intersections annually

The sample is secondary data obtained from (http:/autoaccident.com). The sample collected shows the number of accidents that were caused by red-runners annually in the intersections. The sample contains the number of accidents caused by red-runners in the intersections annually in the last twenty-one years from 2000 to 2020.

Descriptive statistics

The mean number of accidents caused by red-runners in the intersections annually from the year 2000 to 2020 is approximately 158620. The mode is 164125 while the median is 158620. The standard deviation of the data set is 8715.012899 while the variance is 75951449.83. the highest number of accidents registered in my sample is 172550 while the lowest is 145472.

Graphs

From my data, I expect to see how the number of accidents caused by red-runners in the intersections has been changing annually. I am hoping to learn the trend of the number of accidents in the intersections caused by red-runners and also be able to predict the future numbers using my data.

References

Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60.

Sharma, S. K., Kanchan, T., & Krishan, K. (2018). Descriptive statistics. The Encyclopedia of Archaeological Sciences, 1-8.

Scatter Plot

number of accidents caused by red-runners 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 169600 164125 172550 172172 150372 164652 150050 155011 160774 158620 149152 151590 152691 162193 166574 151582 169607 164125 153567 145472 146548

year

number of accidents caused by red-runners

DAT/565: WEEK1- Apply: Statistics Analysis

Assignment Content

• • Insert a new column in the database that corresponds to “Annual Sales.” Annual Sales is the result of multiplying a restaurant’s “SqFt.” by “Sales/SqFt.”
  • Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables.
  • Create a box-plot for the “Annual Sales” variable. Does it look symmetric? Would you prefer the IQR instead of the standard deviation to describe this variable’s dispersion? Why?
  • Create a histogram for the “Sales/SqFt” variable. Is the distribution symmetric? If not, what is the skew? Are there any outliers? If so, which one(s)? What is the “SqFt” area of the outlier(s)? Is the outlier(s) smaller or larger than the average restaurant in the database? What can you conclude from this observation?
  • What measure of central tendency is more appropriate to describe “Sales/SqFt”? Why?

Submit your assignment. Review the Wk 2 – Apply: Statistical Report assignment.
In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Microsoft® Excel®. Answer the questions below in your Microsoft® Excel® sheet or in a separate Microsoft® Word document:

Resources

• Pastas R Us, Inc. Database 
  •  
  • *******BELOW IS THE WK2 ASSIGNMENT TO USE FOR REFERENCE******

SCORE A+ WITH HELP FROM OUR PROFESSIONAL WRITERS – Professional Development Presentation: Descriptive Statistics

Wk 2 – Apply: Signature Assignment: Statistical Report [due Day 7]

Resources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis Assignment

Purpose 

This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.

Scenario: 

Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:

· Median age between 25 – 45 years old

· Household median income above national average

· At least 15% college educated adult population

Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.

The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.

Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.

Report:

Write a 750-word statistical report that includes the following sections:

· Section 1: Scope and descriptive statistics

· Section 2: Analysis

· Section 3: Recommendations and Implementation

Section 1 – Scope and descriptive statistics

· State the report’s objective.

· Discuss the nature of the current database. What variables were analyzed?

· Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.

Section 2 – Analysis 

· Using Excel, create scatter plots and display the regression equations for the following pairs of variables:

· “BachDeg%” versus “Sales/SqFt”

· “MedIncome” versus “Sales/SqFt”

· “MedAge” versus “Sales/SqFt”

· “LoyaltyCard(%)” versus “SalesGrowth(%)”

· In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.

Section 3: Recommendations and implementation

· Based on your findings above, assess which expansion criteria seem to be more effective.Could any expansion criterion be changed or eliminated? If so, which one and why?

· Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?

· Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)

· Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)