Statistical significance test excel

    • [DOCX File]Statistical Tests - Loudoun County Public Schools

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      If you are using a significance level of alpha = 0.05, a two-tailed test allots half of your alpha to testing the statistical significance in one direction and half of your alpha to testing statistical significance in the other direction. This means that .025 is in each tail of the distribution of your test …

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    • [DOC File]Advanced Excel - Statistical functions & formulae

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      It is equal to the significance level of the test for which we would only just reject the null hypothesis. The p-value is compared with the significance level and, if it is smaller, the result is significant. That is, if the null hypothesis were to be rejected at = 0.05, this would be reported as 'p < 0.05'. Range. The highest score for a measure minus the lowest score for a measure ...

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    • [DOC File]Statistical Power - STT-consulting

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      In very basic terms, statistical power is the likelihood of achieving statistical significance. In other words, statistical power is the probability of obtaining a p-value less than 0.05, for example. Obtaining p < 0.05 is exactly what many studies strive for, making the understanding of power calculations “a must”. A power analysis is typically performed before a study is being planned ...

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    • [DOC File]Hypothesis Testing Worksheet

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      Conduct a significance test to see if the true mean is more than the reported average. Use an =0.01. 9. An environmentalist collects a liter of water from 45 different locations along the banks of a stream. He measures the amount of dissolved oxygen in each specimen. The mean oxygen level is 4.62 mg, with the overall standard deviation of 0.92. A water purifying company claims that the mean ...

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    • [DOC File]Excel For Introductory Statistical Analysis

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      Excel For Introductory Statistical Analysis. Europe Mirror Site USA Site . This is a webtext companion site of Business Statistics. Excel is the widely used statistical package, which serves as a tool to understand statistical concepts and computation to check your hand-worked calculation in solving your homework problems. The site provides an introduction to understand the basics of and ...

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    • [DOCX File]Statistics # 1 – Central Tendency and Plotting

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      Repeat the statistical analysis, from question 2., in SPSS and copy and paste the output tables from SPSS into Excel. The SPSS results should be pasted into a separate worksheet named “SPSS” using the “Paste Special -> picture” option in Excel. The Word document “How to perform a dependent t-test in SPSS” will guide you through the necessary steps.

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    • [DOC File]MULTIPLE REGRESSION - Fordham

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      analyze and interpret the computer output for a multiple regression model. test the significance of the independent variables in a multiple regression model. use variable transformations to model nonlinear relationships . recognize potential problems in multiple regression analysis and take the steps to correct the problems. incorporate qualitative variables into the regression model by using ...

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    • [DOC File]Advanced Excel - Statistical functions & formulae

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      It is equal to the significance level of the test at which we would reject the null hypothesis. The p-value is compared with the significance level and, if it is smaller, the result is significant. That is, if the null hypothesis were to be rejected at = 0.05, this would be reported as 'p < 0.05'. Range. The highest score for a measure minus the lowest score for a measure. Regression Line. A ...

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    • [DOC File]Example of statistical analysis

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      Test Statistics – The Shapiro-Wilk test is recommended; however it can sometimes be useful to use multiple tests of normality to ensure the stability of the data (ie. Kolmogorov-Smirnov). Although the Shapiro-Wilk statistic can be calculated by hand, students may also use online resources for simplification. The example data provided in . Student Collected Data from this Experiment. is ...

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    • [DOC File]Statistical Testing - Tech

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      If you do enough statistical tests on something, the odds are that the t-test will show significance on something even though significance is not there. For example, if p=0.05 is taken as the cutoff point, then 1 time out of 20 you will get significance when the underlying distributions are the same. Thus, if you perform 20 t-tests, odds are that one of them will show significance even though ...

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