Statistics Purpose Statement

Due to financial hardship, the Nyke shoe company feels they only need to make one size of shoes, regardless of gender or height. They have collected data on gender, shoe size, and height and have asked you to tell them if they can change their business model to include only one size of shoes – regardless of height or gender of the wearer. In no more 5-10 pages (including figures), explain your recommendations, using statistical evidence to support your findings. The data found are below:

Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of

(1) A study of the number of cars sold looked at the number of cars sold at 500

Prior to this course I have used statistics in my professional life. During my previous employment at the University of Tennessee, College of Veterinary Medicine I worked in the student admissions which made my primary job focus the student application process. This process required me to compile statistical information on our applicant pool for faculty and administrative staff to determine who would be accepted. This statistical data included both categorical data, such as current grade level in undergraduate studies, gender, and ethnicity, as well as numerical data such as age, GPAs, average number of courses taken in a semester, credit hours completed, and test scores (Mirabella, 2011). After the admissions process was completed, these different

To view the research on a nominal scale, the research data can be drawn from the type of class. The word nominal is derived from the root word in Latin for name (Usable Stats, 2013). The name of the class, Psychological Statistics, is the nominal measurement for this research. When conducting this study, the study will only be measured during the course of this specific class. The results could drastically change when considering another type of class such as Quantitative Literacy as the cognitive understanding of such a collegic math class may be more optimal through a different course-delivery format.

In this assignment I will look at the ways in which data is gathered and selected, I will show my understanding of how to interpret data and information, and how I communicate the results of the information analysis.

The information in the table below refers to the 2008 model year product line of BMW automobiles. Identify the Individuals, variables, and data corresponding to the variables in the table below. Determine whether each variable is qualitative, continuous, or, discrete. Please refer to problems #51 and #53 on page 13 for examples.

Assuming unequal variances, the two sampled t-Test was applied on the data sets of female and male shoe sizes with the alpha value of 0.05. The null hypothesis was that the female and male shoe sizes have an equal mean while the alternative hypothesis was that female and male shoe sizes do not have an equal mean. With the degrees of freedom being 27, the t-statistic is -8.16. The probability that -8.16 is ≤ -1.70 is 4.5×10-9 for the one-tailed test. Also, the probability that -8.16 is ≤ ±2.05. is 9.1×10-9 for the two-tailed test. Given that both probabilities are under the alpha value of 0.05, the null hypothesis is therefore rejected, and the alternative hypothesis is accepted at the 95% confidence level.

As an undergraduate student at Claremont McKenna College, I was on the hunt for a career field that provided the perfect fit. Despite my love of mathematics since middle school, it never occurred to me to study anything quantitative. Being a first-generation college student, I had parents who knew of only two career fields worthy of my future: medicine

A pharmaceutical company is testing the effectiveness of a new drug for lowering cholesterol. As part of this trial, they wish to determine whether there is a difference between the effectiveness for women and for men. Using   = .05, what is the value the test statistic?

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Use the given degree of confidence and sample data to construct a confidence interval for the population proportion. 1) Of 346 items tested, 12 are found to be defective. Construct a 98% confidence interval for the percentage of all such items that are defective. A) (3.34%, 3.59%) B) (1.18%, 5.76%) C) (1.85%, 5.09%) D) (0.93%, 6.00%) E) (0.13%, 6.80%) 2) Of 81 adults selected randomly from one town, 64 have health insurance. Construct a 90% confidence interval for the percentage of all adults in the town who have health insurance. A) (71.6%, 86.5%) B) (67.4%, 90.7%) C) (70.1%, 87.9%) D)

In this mathematical circumstance, it is appropriate to use the Normal Model with this data distribution because of how roughly symmetric and unimodal. The summary statistics for the OB Math SAT scores are as follow: the number of values is 287, the mean of the data is 553.62369, the standard deviation is of approximately 65.984512, the median of the data is 540, the range of the data is 390, the minimum value is 360, the maximum value is 750, the first quartile of the data is 510, and the second quartile of the data is 590. To calculate the percent of students that had an SAT math score higher than 560, I used the z-score formula which is z-score= raw score- mean/ standard deviation and plugged the values for each variable. After

Why does the sampling distribution of the mean follow a normal distribution for a large enough sample size, even though the population may not be normally distributed?

On the other hand, my interest in the incorporation of artificial intelligence and machine learning by financial institutions stems from my work as a Credit Risk Analyst for BECU. I recently joined the institution, and am working on a year-long project to integrate the Synergy Component System which will enable increased automation, improved attribution management, and reduced decision times for credit card and auto loans. Beyond testing plans and cases, I am most excited about designing decision matrices by analyzing member data such as credit quality, debt-to-income ratio, membership years, and trade lines to reach a credit decision. While I have had already experienced academic research, this will be my first taste of applied industry research.

This case problem is related to a property purchase strategy. The president of Oceanview is deciding whether to bid for a property to build and sell condominiums. However, this depends on whether the state can change the zoning of the property to permit construction of condominiums. Here, the decision is whether to bid for the property, and chance events are firstly, whether the bid can be successful, and secondly, whether the state will approve the zoning change. To assess the likelihood that the state will approve the zoning change, the president can hire a market research service. Hence, the president is facing another decision as