Term Paper on "Course Analysis: Math and Statistics"

Term Paper 3 pages (1237 words) Sources: 3

[EXCERPT] . . . .

Wasserman (2004) explains that during data analysis, hypothesis test are stated in terms of one condition that the statistician or researcher doubts, and one that they believe. The null hypothesis refers to the statement that will be tested often denoted by 'H0', while the alternative hypothesis 'H1' refers to the one that will be accepted once the former is rejected. Hypothesis testing, therefore, starts with making a statement about the value of a parameter, then goes on to establish whether the statement is true or false. Hypothesis testing is useful in real life situations where decision making involves testing various ideas. These include introducing a new product into the market, investigating the effects of a new drug, or even determining the best teaching methods to be applied in an institution of higher learning. Furthermore, careers in different fields of investments, statistical research, and bureaus of statistics, among many others, make use of hypothesis testing.

Selection of appropriate statistical tests

Statistical tests provide an individual with mechanisms for making quantitative decisions about a particular process. The tests determine whether there is sufficient evidence to reject a null hypothesis. Test statistics are the quantities taken from samples and used as the basis of testing a null hypothesis. Significance levels are also taken into consideration because they incorporate the probability of certain type of errors. Statistical tests include: the F-test, Chi-square test, and Levene test for measuring variability; runs tests and autocorrelation tests for measuring randomness; and measures for skewness and Kurtosis (Anderson, Sweeney and Williams, 2013

Continue scrolling to

download full paper ⤓

). All statistical tests can be applied in the day-to-day operations of a variety of careers to address uncertainties of sample estimates.

Evaluating statistical results

It is important to analyze statistical information in order to avoid misleading results and misinterpretation. According to Downing and Clark (2010), the critical elements that should be applied when evaluating results include the source of the research, objects that were studied, extraneous differences between samples and groups being compared, and the magnitude of any differences. Spreadsheets, frequency distribution tables and graphs can be used to analyze the statistical results. In evaluating real life statistical results, a researcher or statistician has to see if the null hypothesis has been approved, investigate the quality of collection, interpretation and analysis of data and utilize an evaluative means test such as ANOVA to assess the applicability of the samples used (Anderson, Sweeney and Williams, 2013). Qualitative aspects are also analyzed, depending on the field of research. This skill can be utilized by professional statisticians, managers and investors when evaluating business and market trends. It is also useful in careers such as investment analysis, economics, statistics, and research.

Conclusion

Descriptive and inferential statistics can be used to describe statistics in all forms of research, to explain market trends, and to make use of samples when large populations need to be studied. This is useful in the business environment particularly because the success of products and services depends on thorough research on target populations and global markets. Moreover, hypothesis development and testing, and selection of appropriate statistical tests also helps in making quantitative and evidence-based decisions; while evaluation enables individuals to interpret results and make informed conclusions. It is, therefore, accurate to conclude that all the statistical elements we have learnt throughout the course are applicable in real-life situations and they could be critical in our respective career fields.

References

Anderson, D., Sweeney, D & Williams, T. (2013). Essentials of Modern Business Statistics with Microsoft Excel. Boston, MA: Cengage Learning

Downing, D. & Clark, J. (2010). Business Statistics. Hauppauge, NY: Barron's Educational Series, Inc.

Wasserman, L. (2004). All of Statistics: A Concise Course in Statistical Inference.… READ MORE

Download Full Paper

Write a New Paper for Me

How to Reference "Course Analysis: Math and Statistics" Term Paper in a Bibliography

“Course Analysis: Math and Statistics.” A1-TermPaper.com, 2015, https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311. Accessed 5 Oct 2024.

Course Analysis: Math and Statistics (2015). Retrieved from https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311

A1-TermPaper.com. (2015). Course Analysis: Math and Statistics. [online] Available at: https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311 [Accessed 5 Oct, 2024].

”Course Analysis: Math and Statistics” 2015. A1-TermPaper.com. https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311.

”Course Analysis: Math and Statistics” A1-TermPaper.com, Last modified 2024. https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311.

[1] ”Course Analysis: Math and Statistics”, A1-TermPaper.com, 2015. [Online]. Available: https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311. [Accessed: 5-Oct-2024].

1. Course Analysis: Math and Statistics [Internet]. A1-TermPaper.com. 2015 [cited 5 October 2024]. Available from: https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311

1. Course Analysis: Math and Statistics. A1-TermPaper.com. https://www.a1-termpaper.com/topics/essay/math-statistics-course-analysis/2239311. Published 2015. Accessed October 5, 2024.

Related Term Papers: