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Statistics1 - Statistics Project Example

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Examples of such measures are measures of central tendency such as mean, median, mode and measured of dispersion such as standard deviation and range. Inferential statistics are…
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Descriptive and inferential statistics Descriptive statistics are the set of statistical measures that can be used to summarize the data. Examples ofsuch measures are measures of central tendency such as mean, median, mode and measured of dispersion such as standard deviation and range. Inferential statistics are the set of statistical techniques that can be used to derive certain aspects of population based on findings from sample. Difference between sample, population, statistic and parameterIn simplest of terms, sample is a subset of population which is the whole set for which we want to make inferences about.

Generally the sample is used to make statistical conclusion for the population. The calculated measure for sample is called as statistic whereas the same measure for the population is known as parameter.Sampling errorSampling error is the error that occurs when the sample is not a representative of the population. This arises out of incorrect sampling method being used to describe the population. The error means that the statistic for the sample will be different from the parameter for the populationBasic characteristics of experimentAn experiment is a scientific research method in which the researcher controls one or more variables and measures the changes in other variables.

Experimental research is generally used when there is high degree of correlation between the variables. Study typeDr. Jones has conducted an experimental study. Dr. Jones has controlled the variable quality of breakfast by dividing the sample into two groups and administering different quality of breakfast to each. Academic performance is the dependent variable which is studied for both the groups. Scales of measurementNominal v/s Ordinal: While nominal scale is the representation of a descriptive category of the variable, the ordinal scale is the representation of the also contains the magnitude of the order of the value on the scale.

For example, while gender that can only have male or female as the value is a nominal scale, the position of a horse in a race is the example of the ordinal scaleOrdinal v/s Interval: Apart from the ranking in an ordinal scale, the interval scale also the magnitude of the difference between two values in the series. For example temperature on days is an interval variable because we can also measure the magnitude of the difference between the temperatures on two days. Interval v/s ratio: Apart from the measurement of magnitude, the ratio scale also contains the absolute zero value for a variable below which no value can exist.

Example of such a variable will be weight. Summation notationSquare each score, and then add the squared values Add the scores, and then square the sumAdd two points to each score, and then add the resulting valuesAdd the scores, and then subtract 6 points from the total.Summation expressions1.) Square each score, and then add the squared values 2.) Add the scores, and then square the sum3.) Subtract one point from each score, and then add the resulting values4.) Add all the scores

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