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Statistics is a discipline of applied mathematics that entails the collection, description, analysis, interpretation, and data presentation. Mathematical statistics theories rely mostly on linear algebra, calculus, differential, and probability theory.
There are two major branches of statistics which are:
Descriptive statistics describe the properties of a sample and population data. It primarily focuses on the data sample’s variability, central tendency, and distribution.
Variability refers to statistics that show the amount of difference among the elements of a population or sample across the measured characteristics. Some variability includes benchmarks such as variance, range, and standard deviation.
The central tendency means approximating the characteristics of a population or standard sample element. It includes descriptive statistics such as median, mean, and mode.
The distribution is the data’s general shape, which can be elaborated on a chart such as a dot plot or histogram. It entails properties such as skewness, probability distribution function, and kurtosis.
Descriptive statistics also explain the differences between the characteristics observed in the set data elements. It is crucial in understanding the consolidated properties of sample data elements, creating the foundation for hypothesis testing and prediction making using inferential statistics.
On the other hand, Inferential statistics are tools a statistician uses to come up with a conclusion about the sample population characteristic and to decide how accurate they can rely on those conclusions.
Using a sample size and distribution, statisticians can calculate the probability, which measures the variability, central tendency, distribution, and connection between characteristics of sample data. This will provide an accurate picture of the parameters relating to the whole population from which the sample is taken.
The inferential statistic is used to make future predictions and population generalizations by studying a smaller sample. Most social sciences experiments study a small sample population, enabling them to determine how the general population behaves.
Inferential statistics widely uses regression analysis techniques to determine the correlation (strength and nature of the relationship) between dependent and independent variables. The regression model results are mainly analyzed for statistical significance, which means that the results from the finding derived by experimentation are not likely to have occurred by chance but likely to have been caused by a particular issue elaborated by the data.
Descriptive statistics summarize the data set’s characteristics, while inferential statistics enables you to test a hypothesis or evaluate whether your data is generalizable to the larger population.
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Elementary statistics lay a strong foundation for students, preparing them for a more complex level of statistics. Elementary statistics covers basic inferential and descriptive statistics, including developing box plots, stem and leaf plots, and histograms using the Poisson and binomial distributions to calculate individual probabilities and conduct hypothesis testing. We assist students in dealing with elementary statistics homework.
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