In the past, people lived in towns, and traveling and communication with the world were complicated. Therefore, people had little or any choice of food, goods, medicine, leisure activities, or job. The XXI century is characterized by the fast-paced development of communication, technologies, and transportation. As a result, people can meet, communicate, travel, and even run business with partners who live on the other side of the globe. Therefore, the volume of information and the number of choices which people have to deal with have increased. People have to make decisions and choose every day. In the world of multiple choices, statistical knowledge is particularly useful.
Statistics provides methods for generalization of the data. If a person wants to buy an apartment and wants to get the best deal, then statistics can be used. It is necessary to get data on the properties prices and calculate the descriptive statistics. The descriptive statistics calculates mean, median and mode of the price. These are measures of central tendency (Srisvastava et al. 63), which show how much the average apartment costs. The standard deviation and variance indicate how much the data are scattered around the mean value (Srisvastava et al. 78). In case the standard deviation is high, it indicates a presence of luxurious properties and low-quality apartments. The descriptive statistics also indicates the minimum and maximum prices. When an in-depth analysis is required, skewness and kurtosis are applied (the characteristics of symmetry and shape of distribution) (Srisvastava et al. 74). Skewness value helps to indicate if the majority of properties are cheap or expensive, and kurtosis assesses if properties of all price groups are represented equally, or the average-priced ones are the most frequent. Therefore, the descriptive statistics is a powerful way to get a clear understanding of the large arrays of data.
Nowadays, a person can choose where to work. Salary is one of the most important factors that are taken into account when the choice is made. The age of information provides employees with an opportunity to familiarize yourself with the salaries in the field. When a person has data on the salaries at various companies, it is possible to assess if he or she receives an adequate pay. For example, an electrician’s salary is $20/hour with standard deviation $3.5. If a person receives $16, he can assess how many people receive less by using a z-score (Rubin 87):
z=X-MeanStandard Deviation=$16-$20$3.5=-1.1.
Applying the z-scores table, we can find that only 13.6% (Rubin 88) people receive less than $16/hour in this field. Therefore, the worker has a serious reasoning to look for a better-paid job, since the typical salaries in the field are higher.
The profound chapter that is used in business and finance, medicine and tourism is hypothesis testing. A hypothesis is a question that needs to be answered. Statistical methods are applied to answer the question or statistical guess that is set to compare two (or more) groups of data. The examples of hypotheses: “Is there a difference in body mass index of people who live in south and north?” “Is there a decline in oil price during the last two month”. Two hypotheses are set: the null and alternate hypothesis. The null hypothesis states that there is no difference between the two groups, and alternate hypothesis is opposite to the null (Shi & Jian 65). The hypotheses are tested by calculation of a criterion (t-test, F-test, etc.) (Shi & Jian 139). Sometimes, more complicated analysis, called ANOVA (analysis of variance) is applied. ANOVA deals with a comparison of more than two means (Anderson et al. 469).
Although there is much mathematics beyond hypothesis testing (Shi & Jian 69), the modern computer software has been developed to simplify data processing. The most common and widely available are Excel package (Anderson et al. 4) and Statistical Package for Social Sciences (SPSS) (Field 61). When the software package is applied, the researcher has to enter data and choose the type of test. The software assistance is essential when ANOVA is applied since the calculations are complicated (Anderson et al. 469). The programs (SPSS and Excel, or any other) calculates the descriptive statistics, the criterion value, and provides a measure for decision-making. In hypothesis testing, the decision is made basing on the p-value: if p-value > 0.05 then the null hypothesis is accepted, and the alternate hypothesis is rejected, if p-value < 0.05 then the null hypothesis is rejected, and the alternate hypothesis is accepted (Shi & Jian 71). The application of the hypothesis testing is an example of the theory of probability in the real-life situations.
The knowledge of statistics helps to arrange and understand the world of numbers. The statistics provides the scientific methods to analyze, generalize and answer research questions, where comparison of mean values is required. It is particularly important in an everyday decision-making process, where finance issues are involved.
Works Cited
Anderson, David R, Dennis J. Sweeney, Thomas A. Williams, and David R. Anderson. Essentials of Modern Business Statistics with Microsoft Excel. Mason, Ohio: Thomson/South-Western, 2004. Print.
Field, Andy P. Discovering Statistics Using Spss: (and Sex and Drugs and Rock 'n' Roll). Los Angeles [i.e. Thousand Oaks, Calif.: SAGE Publications, 2009. Print.
Shi, Ning-Zhong, and Jian Tao. Statistical Hypothesis Testing: Theory and Methods. Singapore: World Scientific Pub, 2008. Print.
Srivastava, Uma K, G V. Shenoy, and S C. Sharma. Quantitative Techniques for Managerial Decision Making: Concepts, Illustrations, and Problems. New York: Wiley, 1983. Print.
Rubin, Allen. Statistics for Evidence-Based Practice and Evaluation. Belmont, Calif: Brooks/Cole, 2010. Print.
