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Short notes with examples to explain you discriptive statistics ii inferential statistics?
Descriptive statistics give information regarding a data set. For example, any graph, the mean, median, and mode, standard deviation, range, and variance are all descriptive statistics.
Inferential statistics is using a representative sample from a population to say something about that population. For example, for presidential polls, not everyone in the country is called and asked who they plan to vote for. Whoever does the surveying picks a sample that should fairly represent the population as a whole, and just asks those people. Depending on the sample size, the surveyor can then determine how accurate the results are, and use them to generalize to the population as a whole.
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Explain the role of inferential statistic in business?
looking for a simple expanation
Are crime rates descriptive explanatory inferential or exploratory?
Crime rates are typically considered descriptive statistics, as they summarize and provide information about the frequency of crimes within a specific population or area over a given time period. They help to convey a clear picture of crime trends but do not inherently explain the causes or relationships behind those trends. However, when used in conjunction with other data and analyses, they can also contribute to inferential or explanatory studies that explore underlying factors affecting crime rates.
What is the function of subject and its examples?
to explain to the reader
What is the Important of statistics in mathematics?
what I would like to know is the importance of statistics in mathematics in relation to aspects like the mode,median & the mean and how one can explain this in a 2000 word essay
What are the advantages and disadvantages of descriptive statistics?
Descriptive statistics are very useful for showing and summarizing data when any complex models are nit needed. However, it does not explain the relationship between two or more pieces of data and it does not leave any room to explain randomness in the data.
