# BUS 308 Week 5 Final Paper

**Topics:**Statistics, Statistical hypothesis testing, Statistical inference

**Pages:**6 (1142 words)

**Published:**November 17, 2014

Statistics Overview

Jennifer Shanley

BUS 308-Statistics for Managers

Professor Wells

November 1, 2014

Statistics Overview

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 the statistical principles are all statistical procedures that are more advanced in nature. Even though the data can be applied to several areas of the human aspiration to implement the theory and methods of modern statistics to various different fields. Many useful elements were included in this course like descriptive statistics, inferential statistics, hypothesis development and testing, selecting appropriate statistical tests and evaluating the statistical results; which aides me to make better decisions in my personal and professional life. The intention of this paper is to be able to review each of these individual elements that we studied throughout this course. Descriptive Statistics:

Descriptive statistics are typically utilized for describing the general features of the information received from a study. The results provide a brief summary of sample and measures. This type of statistics along with a simple graphic aid, creates the basis for nearly all quantitative data analysis. It is also used for presenting quantitative descriptions of data in a comprehensive and manageable form (Schlaifer, 1982). In a research study, there is a possibility of several different measures or it can be a scenario where we are able to measure a lot of people on any form of measure. Descriptive statistics helps us to present a large quantity of data in a much more manageable and realistic form. Each statistic in the descriptive form lowers the quantity of data into a much simpler summary. Inferential Statistics

Inferential statistics helps us to analyze predictions, inferences, or samples about a specific population from the observations that they make. “With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone” (Trochim, 2006). The goal for this type of data is to review the sample data to be able to infer what the test group may think. It does this by making judgment of the chance that a difference that is observed between the groups is indeed one that can be counted on that could have otherwise happened by coincidence. In order to help solve the issue of generalization, tests of significance are used. For example, a chi-square test or T-test provides a person with the probability that the analysis’ sample results may or may not represent the respective population. In other words, the tests of significance provides us the likelihood of how the analysis results might have happened by chance in a scenario that a relationship may not exist between the variables in regards to the population that is being studied. Hypothesis Development and Testing:

Hypothesis testing and development provides a baseline for taking ideas or theories that were initially created by another person in regards to the markets, economy, or investing and then determining if the ideas are true or false. Specifically the hypothesis testing and development to help decide whether the ideas that were tested are probably true or probably false as the conclusions are made on the hypothesis testing basis, are not necessarily made with a confidence level of 100%. In the process of hypothesis testing, we use different degrees of confidence, such as...

References: Fraser, D. A. S. (1956). Nonparametric methods in statistics.

Leach, C. (1979). Introduction to statistics: A nonparametric approach for the social sciences. New York: Wiley.

Schlaifer, R. (1982). Introduction to statistics for business decisions. RE Krieger Publishing Company.

Trochim. (2006). Inferential Statistics. Retrieved September 28, 2014, from http://www.socialresearchmethods.net/kb/statinf.php

Walpole, R. E. (1974). Introduction to statistics (p. 340). New York: Macmillan.

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