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 parameter
In 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 error
Sampling 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 population
Basic characteristics of experiment
An 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 type
Dr. 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 measurement
Nominal 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 scale
Ordinal 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 notation
Square each score, and then add the squared values
Add the scores, and then square the sum
Add two points to each score, and then add the resulting values
Add the scores, and then subtract 6 points from the total.
Summation expressions
1.) Square each score, and then add the squared values
2.) Add the scores, and then square the sum
3.) Subtract one point from each score, and then add the resulting values
4.) Add all the scores Read More
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