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Multivariate analysis involves a set of techniques to analyse data sets on more than one variable. Many of these techniques are modern and often involve quite sophisticated use of computing tools. such analyses refer to all statistical methods that simultaneously analyse multiple measurements on each individual or object under investigation. Hence, any analysis simultaneously involving analysis of more than or equalto two variables can loosely be considered multivariate analysis.
This unit will provide a list of such analyses ill order to help decide when to use a given statistical technique for a given type of data or statistical question. It also gives a brief description of each technique. It is organized according to the number of data sets to analyze: one or two (or more). With two data sets we consider two cases: in the first case, one set of data plays the role of predictors or independent.variablesand the second set of data corresponds to measurements or dependent variables; in the second case. the different sets of data correspond to different sets of dependent variables.
Charts when the Mean and the Standard Deviation are not known We consider the data corresponding to the example of Piston India Limited. Since we do not know population mean a
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Each section of the SAT test is supposed to be distributed normally with a mean of 500 and a standard deviation of 100. Suppose 5 students in a class took the SAT math test. They r
Analytical Approach We will illustrate this through an example. Example 1 A firm sells a product in a market with a few competitors. The average price charged by the
A marketing research firm was engaged by an automobile manufacturer to conduct a pilot study to examine the feasibility of using logistic regression for ascertaining the likelihood
Large Sample Test for Mean A random sample of size n (n > 30) has a sample mean . To test the hypothesis that the population mean μ has a specified value μ 0 let us formu
Explanation of descriptive statistics Describe what these descriptive statistics show or what recommendations you would create to AIU. What information do you now have as a re
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Test for Equality of Proportions For example, we may want to test whether the percentage of smokers (p 1 ) among the males equals the percentage of female smokers (p 2 ). W
Statistics Can Lead to Errors The use of statistics can often lead to wrong conclusions or wrong estimates. For example, we may want to find out the average savings by i
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