Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions and misused for other reasons in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics comprise applied statistics. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject. Stats or statistics are used in all sports as well as in all aspects of life. Statistics is used in sports to measure a players ability in specific areas of the game. Stats or statistics are used in all sports.

Statistical analysis is best organized into two subsets: descriptive statistics and inference statistics. Descriptive statistics is used to summarize the data by organizing it graphically or numerically. Charts and graphs are used in descriptive statistics to show variation in the sample, or a chosen subset of the population being observed. An example of this in sports is in baseball a chart shows the percentage or times or amount of times a ball is hit. Numerically organized data is often displayed as standard deviation or as a mean. A mean is simply an average, while standard deviation is the measure of statistical dispersion, or how the information gathered relates to the mean of the data. One stat that uses mean is earned run average (ERA). ERA is the mean of earned runs given up by a pitcher per nine innings pitched. It is...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the...

...of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum
21430
From the table above, the total number of passengers for route 1 is 44,266, route 2 is 29,131 and route 3 is 21,430 and the total numbers of passengers for 3 routes are 94,827.
Although route 1 has the highest number of passengers and flights but it has the lowest means of passengers among the 3 routes. From...

...Abstract
This paper will indicate the economical and statistical scope of the sports industry and how much students at the University of La Verne are spending and/or willing to spend on sports entertainment. The objective of this project is to experiment and analyze La Verne’s student’s consumption on a variety of different sports merchandise/services. Our group conducted an on campus survey with approximately 200 data. Based on these data; we were able to extract variations and study it using statistical analysis, hypothesis testing, and regression analysis.
Introduction
Understanding sports entertainment and how much consumers are willing to spend on sports is imperative for businesses to research and survey. The average Americans spent on sports entertainment in 2010 was approximately 25.4 billion, based on the U.S. Bureau of Labor Statistics reported in August 2012. (U.S. BLS) Sports entertainment spending dropped 8 percent from 2009 as consumers tightened their belts in an uncertain economy. People spent less on sports events, sports apparel, and different sports merchandise. However, at the same time, Americans spent more on home-based entertainment such as cable television and watching sports at home. We put our hypothesis to test by inquiring different variations. Here is an exhibit of...

...compliments the regular mathematics and therefore both are tested in primary schools. Mathematics is the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where teachers expect the transference of concrete to abstract thinking would have occurred.
A common theory by many primary school teachers is ‘Students perform better in Mathematics than Mental math. Mental math is something that has to be developed and involves critical thinking. Mental math requires quick thinking and the student must solve the problem in their minds whereas in regular mathematics, the problem can be solved visually. Therefore, teachers should take these factors into consideration while testing and marking students in these areas.’
In this study, the statistics of 30 students of a standard 3 class of San Fernando Boys’ Government School will be analysed to determine the truth of this theory.
DATA COLLECTION METHODS
Mathematics and mental mathematics marks of term 1 of the class of 2013 were obtained from a Standard 3 teacher of San Fernando Boys’...

...Take Five Sports Bar and Grill has established a successful presence in the food and beverage service industry. The flagship location in suburban Anytown (Medlock Bridge) will gross in excess of $2 million in sales in its first year of operation, ending July 1996. First year operations will produce a net profit of $445,000. This will be generated from an investment of $625,000 in initial capital. Since 10 months of operations have already been completed the confidence level for final first year numbers is extremely high. The first 10 months of start-up costs, sales revenues, and operating expenses are actual.This restaurant industry is very large and sometimes hard to get exact numbers. There are many categories of restaurants so I outlined Services sector and the restaurant industry according to Yahoo finance. “The nation's 900,000 restaurants should hit $476 billion in sales in 2005, according to the National Restaurant Association's 2005 Restaurant Industry Forecast”. Restaurants employ12.2 million, this is 9% of the workforce in the United States, and the industry is the largest employer besides government. These numbers include single owner restaurants to the largest franchises in the world.
The growth trends for the restaurant industry are forecast to advance 4.9% in 2005. Analyst predict that the U.S. Restaurant Industry which created, on average, about 270,000 new jobs per year during the last 10 years is on track to add 1.8 million new jobs...

...Statistics 1
Business Statistics
LaSaundra H. – Lancaster
BUS 308 Statistics for Managers
Instructor Nicole Rodieck
3/2/2014
Statistics 2
When we hear about business statistics, when think about the decisions that a manager makes to help make his/her business successful. But do we really know what it takes to run a business on a statistical level? While some may think that businessstatistics is too much work because it entails a detailed decision making process that includes calculations, I feel that without educating yourself on the processes first you wouldn’t know how to imply statistics. This is a tool managers will need in order to run a successful business. In this paper I will review types of statistical elements like: Descriptive, Inferential, hypothesis development and testing and the evaluation of the results. Also I will discuss what I have learned from business statistics.
My description of Descriptive statistics is that they are the numerical elements that make up a data that can refer to an amount of a categorized description of an item such as the percentage that asks the question, “How many or how much does it take to “ and the outcome numerical amount. According to “Dr. Ashram’s Statistics site” “The quantities most commonly used to measure the dispersion of the values about...

...
MBA 501A – [STATISTICS]
ASSIGNMENT 4
INSTRUCTIONS: You are to work independently on this assignment. The total number of points possible is 50. Please note that point allocation varies per question. Use the Help feature in MINITAB 16 to read descriptions for the data sets so that you can make meaningful comments.
[10 pts] 1. Use the data set OPENHOUSE.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether style of home and location are are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 37.159, DF = 3, P-Value = 0.000
Likelihood Ratio Chi-Square = 40.039, DF = 3, P-Value = 0.000
The P value associated with out chi square is 0.00 and the Alpha level is 0.05 so we reject the null hypothesis. The P- value is less than the alpha level. So, we conclude that style of homes and locations are not related.
[10 pts] 2. Use the data set TEMCO.MTW in the Student14 folder. Perform the Chi
Square test for independence to determine whether department and gender are related. Use α = 0.05. Explain your results.
Pearson Chi-Square = 1.005, DF = 3, P-Value = 0.800
Likelihood Ratio Chi-Square = 1.012, DF = 3, P-Value = 0.798
The P-value associated with out chi square is 0.800 and the Alpha level is 0.05 we can see that we are unable to reject the null hypothesis. The P- value is greater than the alpha level. So, we conclude that departments and gender are related..
[30 pts] 3. Use the data set...

...STAT 600 Statistics and Quantitative Analysis
PROJECT: Stock return estimation
The project must be done by 6-15 a.m. October, 16th. You should submit your projects before the class begins. This is a group project. Read the course outline for general guidelines. Good luck!
The project is closely related to Lectures 1-5 of the class.
Today is September 15, 2013 and you have just started your new job with a financial planning firm. In addition to studying for all your license exams, you have been asked to review a portion of a client’s stock portfolio to determine the risk/return profiles of 12 stocks in the portfolio. Unfortunately, your small firm cannot afford the expensive databases that would provide all this information with a few simple keystrokes, but that’s why they hired you. Specifically, you have been asked to determine the monthly average returns and standard deviations for the 12 stocks for the past five years.
The stocks (with their symbols in parentheses) are:
Apple Computer (AAPL) Hershey (HSY)
Archer Daniels Midland (ADM) Motorola (MOT)
Boeing (BA) Procter and Gamble (PG)
Citigroup (C) Sirius XM radio (SIRI)
Caterpilar (CAT) Wal-Mart (WMT)
Deere&Co. (DE)...

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