BUS 308 Week 5 Final Paper

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.

I believe that in the verge of realization, in everyday life’s undertaking we are facing and practicing statistics. I was being into a serious dedication of understanding the underlined concepts of statistics and the necessary usefulness in conducting a survey. In fact, throughout the course, I did learn many factors that became useful in contacting a survey research. according to Walker et al. (2011). However, my success could not be possible without the appreciation and support of my teachers, discussion groups, and class presentations.in addition, the misguided notion of statistics being a tough course was proven otherwise since I realized that statistics make a lot of sense not only in survey research in personal life, especially in budgeting and planning for individual routines. Furthermore, the following paper provides a vivid explanation of my reflection of the survey class, with more attention paid to the concepts of statistics.

The topic of interest I will be covering in this research paper is the statistical information about the

The researcher through the data collected will test following hypothesis in order to accept or reject them.

There are various types of statistical validities that are applicable to research and experimentation. The three different validities in which I will be explaining about are, internal, external, and construct. Each of these validities is essential in order for the experiment to give accurate predictions and reach valid conclusions. I will also be explaining panel data, cross sectional data, experimental data, and survey experimental data. Lastly, I will explain how one of these data could be useful to me in resolving an issue that I may encounter in life.

Descriptive statistics will be used to present summaries of data collected when necessary. Inferential statistics will be used to test the research

William E. Martin, Krista D. Bridgmon (n.d.) Quantitative and Statistical Research Methods: From Hypothesis to Results, : Jossey

We try to conclude from the evidence what a sample group may think. For inferential statistics, we use it to make decisions on the probability of the observed difference between the groups and if it is dependable or just happened by chance based on the group. “…we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simple to describe what’s going on in our data (socialresearchmethods.net).” An example of inferential statistics is, a gym teacher wants to know the average amount of three point shots the students in this particular school can make in 30 seconds, he chooses only the students on the basketball team to sample it, the results he get would not be a representative sample simply because that does not represent a random sample of the entire school, but the results he gets and writes from this test would be considered an inferential statistic.

Overall LTA discovered statistics consist of calculating everyday numerical data. Statistics consist of classifying, analyzing, summarizing, organizing, and interpreting numerical data, according to (McClave, Benson, & Sincich, 2011, p. 3). The team also discovered the following from the authors among other pertinent information:

“Descriptive statistics are used to describe the basic features of the data in a study…which provide summaries about the sample and the measures. With descriptive statistics you are simply describing what is or what the data show and present quantitative description in a manageable form.” (William, M. K., 2006).

Descriptive statistics can provide a variable summary of the collected samples and measure data for the products. Organization can able to describe what data is an actually presented with the help of descriptive statistics. (Goos & Meintrup, 2015 )

According to Bennett (2009), the biggest difference between descriptive and inferential statistics is that descriptive statistics "deals with describing raw data in the form of graphics and sample of statistics" and inferential statistics "deals with estimating population parameters from sample data." This means that inferential statistics would be an estimate because the data would be estimated from sample data rather than using specific data whereas descriptive statistics would be more accurate. An example of descriptive statistics would be trying to find an average of something such as a G.P.A. or your overall grade in a class.

"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" (Understanding descriptive and inferential statistics, 2012, Laerd). Examples of descriptive statistics include an analysis of central tendency (the position of most members of the group in a particular category, such as age) and measures of spread (the range of members of a group, such as in terms of their various ages). Inferential statistics are often used when not all members of the group can feasibly be tested. "Inferential statistics are techniques that allow us to use these samples to make generalizations about the populations from which the samples were drawn," although the sample must accurately represent the population (Understanding descriptive and inferential statistics, 2012, Laerd). "Both descriptive and inferential statistics rely on the same set of data. Descriptive statistics rely solely on this set of data whilst inferential statistics also rely on this data in order to make generalisations about a larger population" (Understanding descriptive and inferential statistics, 2012, Laerd).

Welcome back! This power point is not as complex or as long as the previous power point. However, we’ll review very interesting concepts that you have heard before, such as estimation, hypothesis testing, and statistical significance. These are foundational concepts that will be used when we conduct inferential statistical techniques. I hope that you find the powerpoints helpful.

The use of statistical analysis is something that has become critical in today 's society. You cannot visit a grocery store or watch television without being introduced to some statistical information that was just discovered: the rising number of teen pregnancies, the average salary of a large corporations ' CEO, or something more subtle such as the fluctuations of political opinions. There are millions of dollars being spent to analyze information that is readily available for anyone looking, in order to condense this knowledge into a more manageable form. Data is meaningless to most people unless it has been refined into readable figures and graphs, and laid out so that the important bits are visible.