Essay on What have you learned about Statistics

The descriptive statistic is a brief descriptive co-efficient which tells about all the given data which can be a representation of a single or a complete data. This descriptive statistic is further broken down into the measures of a central tendency and measures of variability as well. Now, that includes measures of central tendency? It includes standard deviation, median, mode. And now comes to measures of variability which includes standard deviation, minimum and maximum variables, and variance and last but not the least it includes skewness. (Statistics.laerd.com, 2018)

In short, descriptive statistics help in describing as well as understanding about the features of specific data through giving of the short summaries regarding the measures and sample of the data. Among all the descriptive statistics, most recognized ones are the median, mean, mode. All these terms are being used at almost every stage of mathematics as well as statistics. Therefore above-mentioned terms are the most recognized ones because of their regular and constant use in the two subjects. Apart from them, there are many of the less important as well as less common type of terms related to descriptive statistics that are not much recognized and not important as well.

Descriptive statistics are being used by the students as well as the people to repurpose all of the data set that is hard to understand. Along with this to summarize the data and make it short which looks large and not easy to be understood. For example, GPA is a good example of the descriptive statistics which tells about the different class tests, exams, assignments in a combined and compiled form.Now the question here comes that how descriptive statistics can be measured? They can be measured through central tendency or measures of variability. Now, these two measures require graphs, tables, and general discussion to make people understand about the analyzed data. They can get to know about it easily without getting panic. (Socialresearchmethods.net, 2006)

Inferential statistics is a part of two main branches of the statistics. This kind uses a simple set of data which is mostly taken from the population living in a certain area to make inferences about and describe the population living in a particular area. This kind is valuable in a case when it is not easy to get information and examine every single person in a population. For example, for knowing about the diameter of each nail which is being manufactured in a mill is one impossible thing. So inferential statistics can help by using the information from the given sample to know to make generalizations about the diameter of every individual nail which is being manufactured. (Support.minitab.com, 2017)

Hypothesis development and testing of Statistics

The hypothesis is a tentative guess which can be developed with any of the statement. It doesn’t become a hypothesis until or unless it is being tested through experiments and after it when positive results are being obtained it means a hypothesis which was being developed is right. The hypothesis is basically developed by observing any of the condition or scenario and it remains a statement before testing. Now there are two kinds of methods for the developing of hypothesis which are:

Qualitative hypothesis depends on the quality of a statement. It is being generated in which testing cannot be performed like fields which are not part of science. In this kind of hypothesis, words are being used like how and what. They contain open-ended questions and are without any kind of reference. They focus on a single use.

Quantitative hypothesis depends on the quantity and they are being used in the projects which are research-based. They require proper testing through lab experiments and in this approach references are required. (Prasad, 2001)

Now comes the testing of hypothesis. The statement becomes a hypothesis when test and results come positive. It includes Verification, justification, validity, repeatability, and falsification. If the result comes positive it further requires testing again and again to know the final result of the statement. Two possibilities occur:

When nothing happens and the result comes negative it is called a Null Hypothesis.

When the result comes positive and something happens it is known as the Alternative Hypothesis

Hypothesis testing is based on four steps which are:

Stating of the hypothesis which can be null or Alternative.

Setting up of criteria for specific discussion

Collection of the data

Evaluation of the Null Hypothesis.

There are chances that error comes while the testing of a statement due to which repeatedly tests is being formed to avoid any error in the hypothesis.

Selection of the appropriate statistical tests

Selection of the appropriate statistical tests is quite a big problem for the students. In it, the first step which should be done is defining of the level of measurement of every single variable which is required to be needed in the analysis. Variables can be categorical or nominal, ordinal or rank-ordered. This test needs to be done on both the variables whether they are independent or dependent variables. Then make sure to select the correct statistical analysis in which it requires the complete clarification that what is supposed to be known. So there are different terms in the stats which require different tests and without applying proper tests it is not possible to get results. (Veves, 2018)

Evaluation of the Statistical results

The analysis is the main part. If it is not being done properly then all the above work is of no use. But how evaluation can be done? Many people and students don’t get to know about it. Statistical analysis is a quantitative method which is used to find out about the different probabilities between the sets of data and results of data. Now data can become from any of the natural as well as social sciences. Statistical analysis is being used to put emphasis and elaboration on the patterns and trends which are found within the research of a topic.

 Here is its example, it any of the doctors wants to know about the drug that how much effective is it and how early it can cure patients he or she would utilize statistical analysis to see about the effectiveness of a drug. So analysis is very important no matter what field it is. Investigating the data is a very important task and requires proper tests and steps without which one is not able to do the further task and previous work would be also of no more importance. So in applying statistical analysis, one should be well aware of all the terms and steps. The researcher should also know from where he or she is getting the data. If the analysis is not being done properly than hypothesis can also get failed. So at the end here I just want to add that before applying any of the tests or analyzing it, one should know about all the terms which are being used in stats because without knowing them one can’t perform further work no matter what kind of it is. (Statistics solutions.com, 2018)

References of Statistics

Prasad, S. (2001). DEVELOPING HYPOTHESIS And research questions . 1-30.

Socialresearchmethods.net. (2006). Descriptive Statistics. Retrieved from https://www.socialresearchmethods.net/kb/statdesc.htm

Statistics.laerd.com. (2018). Descriptive and Inferential Statistics. Retrieved from https://statistics.laerd.com/statistical-guides/descriptive-inferential-statistics.php

Statisticssolutions.com. (2018). How to Select the Appropriate Statistical Analysis. Retrieved from http://www.statisticssolutions.com/how-to-select-the-appropriate-statistical-analysis/

Support.minitab.com. (2017). What are inferential statistics? Retrieved from https://support.minitab.com/en-us/minitab-express/1/help-and-how-to/basic-statistics/inference/supporting-topics/basics/what-are-inferential-statistics/

Veves, A. (2018). Evaluating the Quality of Data Through Statistical Analysis. Retrieved from https://www.acfas.org/Physicians/Content.aspx?id=674