Descriptive and Inferential Statistics

The first question to ask is, what is the source of the data? You need to consider who is making the claim, and whether or not they are experts on the subject. After answering the first question, one must

through the use of statistics and figures. This article relates to all other articles used

 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.

The last few weeks we covered descriptive statistic: the central tendency, variability, correlation and Z-score. Today’s session is a little bit different, we will be talking about statistical significance. Statistical significance is the level of risk one is willing to take to reject or accept a null hypothesis while it is true and it separate random error from systematic error. When doing a study or research, the statistical significance shows that the difference obtained were not caused by chance. Inferential statistics, the T-test, partition noise from bias by studying a random sample than the population in which we are interested and from the results we infer. The advantage of using sample than a population, it is convenient, saves time, energy and money because n is smaller than population and above all it helps to control systematic and random errors. When we are making a conclusion, we should have a certain confidence or probability of being right and that is called the alpha level; which the risk you are willing to

When we look around us, we may not recognize that statistics is all around. Before I began to take this course “Statistics for Managers” I was not aware of how statistics actually worked. The first idea that came to my mind about statistics was probability. Not knowing statistics and probability are related because they both determine a possible outcome. Throughout this course I have learned what statistics is and how it works. In this paper, I will describe descriptive and inferential statistics, hypothesis developing and testing, the selection of statistical tests, and how to evaluate statistical results in analyzing data.

This report implements material covered from Chapters 4 – 6: Measures of Central Tendency; Measures of Dispersion; and Probability Distribution. The format in the report uses a question and answer narrative to clarify presentation. The report aims to answer the instructor’s questions for “Assignment 2” and information was extracted from two assigned research studies.

On the first day of school, Mr. Serwach’s AP Statistics class participated in an anonymous survey. Nine students answered questions ranging from their age to the number of AP classes they have taken to the number of states they have visited. The purpose of the survey was to gather some data about the class so the students could demonstrate their writing and analysis skills. Based on the results, several conclusions can be drawn to describe the population (which is just the 3rd-period statistics class because the results do not apply to anyone other than the students in the class). For example, the class is likely composed of 11th and 12th graders since the ages of the class range from 16 to 17 years old. Another speculation is that the

Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire population or a sample of it. Descriptive statistics are broken down into measures of central tendency and

3) The performance of personal and business investments is measured as a percentage, return on investment. What

Introduction, pg.4 5. Question, pg.5 6. Purpose, pg.6 7. Variables, pg.7 8. Hypothesis, pg.8 9.

The purpose of the assignment is to review basic hypothesis testing and regression techniques. There is an appendix in your textbook, Appendix C: Using Excel to Conduct Analysis, which may help you with running regressions in Microsoft Excel. You may also wish to use a basic statistics text for guidance if needed. I have also provided you with a table with the t distribution.

*For accurate inference, researchers need to analyze data drawn from representative samples. Discuss some of the practical limitations to doing so for qualitative and quantitative approaches.

When analyzing data, such as the marks achieved by 100 students for a piece of coursework, it is possible to use both descriptive and inferential statistics in your analysis of their marks. Typically, in most research conducted on groups of people, you will use both descriptive and inferential statistics to analyses your results and draw conclusions. So what are descriptive and inferential statistics? And what are their differences? Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way such that, for example, patterns might emerge from the data. Descriptive statistics do not, however, allow us to make conclusions beyond the data we have analyzed or reach conclusions regarding any hypotheses we might have made. They are simply a way to describe our data.

What inferential tests were used in the analysis of data? How are the the tests appropriate for the research questions?

In terms of independent variables, by referring to the Appendix, figure 1 reveals the summary of the sample; it also