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Measures of Dispersion - Alan Neustadtl @ The University of MD
Measures of Dispersion - Alan Neustadtl @ The University of MD

... ™A deviation from the mean can be identified as having a certain amount of force away from the mean. ™We do not know necessarily what factors are at work to make an observation deviate from the mean, but we can measure the actual deviation for each case. ™Therefore, the value of any observation is c ...
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... Conduct the appropriate statistical test stating any assumptions made in the test. So here you have numerical data and you are comparing two samples, so you'll do a 2 sample t-test. The test will be 1-tailed since the experimenter indicates plants with galls should be shorter Ho : μno = μgall Ha : μ ...
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Word - ASDL Community

... The range is the difference between the sample’s largest value and its smallest value. A variable’s interquartile range, IQR, spans the middle 50% of its values. To find the IQR, we order the data from smallest-to-largest, and separate it into two equal parts; if the sample has an odd number of valu ...
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... are therefore called non-parametric or distribution free as the distribution of the parent population is either assumed to be unknown or unable to be described by one or more parameters (remember the mean and standard deviation parameters used to define our normal distribution or the degrees of free ...
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INSTITUTE OF BANKERS IN MALAWI DIPLOMA IN BANKING

... Two groups A and B consist of 100 people each who have same amounts of bank loan. An interest rate discount is given to group A, but not group B (control group). The groups are otherwise treated the same by the bank. It is found that 75 people in group A repay the loan before the expiry of the loan ...
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Question 1 4 points Save A study of 200 apple trees showed that the

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SECTION I Time: 1 hour and 30 minutes Number of questions: 40

University of Pittsburgh Statistics Curriculum
University of Pittsburgh Statistics Curriculum

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Student's t-test

A t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution if the null hypothesis is supported. It can be used to determine if two sets of data are significantly different from each other, and is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known. When the scaling term is unknown and is replaced by an estimate based on the data, the test statistic (under certain conditions) follows a Student's t distribution.
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