Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions and misused for other reasons in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both
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Statistical dispersion is measured by a number system. The measure would be zero, if all the data were the same. As the data varies, the measurement number increases. There are two purposes to organizing this data. The first is to show how different units seem similar, by choosing the proper statistic, or measurement. This is called central tendency. The second is to choose another statistic that shows how they differ. This is known as statistical variability. The most commonly used statistics are the mean (average), median (middle or half), and mode (most frequent data). After the data is collected, classified, summarized, and presented, then it is possible to move on to inferential statistics if there is enough data to draw a conclusion. Statistical inference is the second part of statistics. Statistical inference uses the data that was gathered and organized by descriptive statistics in order to make a logical inference or conclusion. There are two branches of inferential statistics: Bayesian inference and frequency probability. Bayesian inference uses the scientific method to increase the probability that a hypothesis or theorem might be true by presenting factual information. By collecting evidence, the credibility of a hypothesis can change greatly. Evidence can be collected to prove, or disprove the hypothesis. A hypothesis that has been supported by enough evidence should be accepted as true, and a hypothesis that has been rejected by enough evidence

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Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of

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## 1. What Are Descriptive Statistics and How Do They Differ from Inferential Statistics?

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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

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Statistics involves framing questions in a context, then collecting and analyzing data for interpretation. Probability is about chance and fairness with assigned values. Many mathematics instructors teach this discipline in a procedural manner, causing students to miss its essence.

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The use of computerized statistical analysis has developed into a vital tool in the world of sports. Using data analytics to project player abilities, indicative of their potential future performance, is now an important part of team decision-making. This analysis can provide information that makes the difference between adding a quality player, as opposed to one who does not perform up to expectations.

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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.

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It has been identified that through sports psychology one can improve their physical ability and performance. Sports psychology is the study of how the mind, mental states and behaviour effect sporting performance. There are several sport psychology techniques, which have helped me become a better volleyball player. These techniques include planning for performance, controlling arousal levels, mental rehearsal and concentration.

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Statistical procedures are important part of any research. Statistics provides us with a tool that, help us to better understand the large and complex amounts of data that, is gathered by other during a research. Statistics are used in many different fields of study from medical research, behavioral research, and political polls, among others. More so, statistics are often used to add credibility to research studies, or to an argument, as well as, in some cases it helps us justify decisions that we make (Hebl, n.d.).

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In earlier days sports psychology was mostly concerned with developing assessment methods that would identify those people with the potential to become serious superior athletes. Today the focus is on psychological training, exercises that strengthen the mental skills that will help athletic performances on the path to excellence. These skills include mental imagery and focus training. If an athlete is serious about becoming the best he or she can possibly be, the most essential ingredient is commitment to practice the right things. It takes incredible commitment to reach the top: a commitment to rest and train the body so it can perform under the most demanding conditions and a commitment to train the mind to

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There are many repercussions that are projected upon both men and women when they enter into a sport that typically isn’t thought of as gender appropriate. Some of those cultural and social stigmatisms may be abandonment by your peers, and friends questions regarding your sexuality, and even in some cases criticism as to how you are living your life. In some cases, it may lead to you not being accepted by either group, theone whose norems you are not following, of as well as the one with whom you are trying to get involved. This paper will address all of these issues and how these seemingly negative situations can, will, and are, leading to growth. It will also discuss how this is a situation where repercussions are

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