what is the examples of statistics?
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An example of statistics is a report of numbers saying how many followers of each religion there are in a particular country. An example of statistics is a math class offered in high schools and colleges.
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['Descriptive Analysis. Descriptive analysis provides information on the basic qualities of data and includes descriptive statistics such as range, minimum, maximum, and frequency. ... ', 'Measures of Central Tendency. ... ', 'Standard Deviation. ... ', 'Inferential Analysis. ... ', 'Normal Distribution. ... ', 'Non-Normal Distribution.']
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Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data.
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Statistics are aggregates of facts. Statistics are numerically expressed. Statistics are affected to a marked extent by multiplicity of causes. Statistics are enumerated or estimated according to a reasonable standard of accuracy.
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The Importance of Statistics. ... Statistical knowledge helps you use the proper methods to collect the data, employ the correct analyses, and effectively present the results. Statistics is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions.
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Standard analysis tools of inferential statistics The most common methodologies in inferential statistics are hypothesis tests, confidence intervals, and regression analysis. Interestingly, these inferential methods can produce similar summary values as descriptive statistics, such as the mean and standard deviation.
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It consists of aggregates of facts: In the plural sense, statistics refers to data, but data to be called statistics must consist of aggregate of certain facts. A single and isolated fact or figure like, 60 Kgs. weight of a student or the death of a particular person on a day does not amount to statistics.
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Misuse of statistics. Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental.
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['They need to estimate how closely an observed distribution matches an expected distribution. This is referred to as a “goodness-of-fit” test.', 'They need to estimate whether two random variables are independent.']
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Some examples of quantitative data are price , income , weight , temperature, height , length etc. And some examples of qualitative data are beauty of individual, intelligence of people etc…
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There are many different types of tests in statistics like t-test,Z-test,chi-square test, anova test ,binomial test, one sample median test etc. Parametric tests are used if the data is normally distributed .
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A Statistic Is A Numerical Measurement Describing Data From A Population A Parameter Is An Aspect Of An Individual Subject Or Object Being Measured.
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Statistics is a term used to summarize a process that an analyst uses to characterize a data set. If the data set depends on a sample of a larger population, then the analyst can develop interpretations about the population primarily based on the statistical outcomes from the sample.
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Statisticians use summary measures to describe the amount of variability or spread in a set of data. The most common measures of variability are the range, the interquartile range (IQR), variance, and standard deviation.
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Types of Nonparametric Tests. When the word “parametric” is used in stats, it usually means tests like ANOVA or a t test. Those tests both assume that the population data has a normal distribution. Non parametric do not assume that the data is normally distributed.
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Statisticians use sample statistics to estimate population parameters. For example, sample means are used to estimate population means; sample proportions, to estimate population proportions. An estimate of a population parameter may be expressed in two ways: Point estimate.
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['Statistics, Calculus, Linear Algebra and Probability. A) Statistics contain tools that are used to get an outcome from data. ... ', 'Programming Knowledge. Being able to write code is one of the most important things when it comes to Machine Learning. ... ', 'Data Modeling.']