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Introduction to hypothesis testing
Introduction to hypothesis testing

... in the population from which the sample was drawn, no such relationship or differences exist. [...] the statistical significance of a result tells us something about the degree to which the result is "true" (in the sense of being "representative of the population").” [http://www.statsoft.com/textboo ...
Glossary of statistical terms
Glossary of statistical terms

Exam #2 - TAMU Stat
Exam #2 - TAMU Stat

... in Yosemite national park. 20 trees were randomly selected and measured. The p-value for the test statistic B. 0.1457 was 0.23. Your boss wants to know what the number C. 0.3085 0.23 means. It is D. 0.0228 A. the probability that the null hypothesis is true. E. 0.9772 B. the probability of making a ...
Homework1
Homework1

... 2. Open the breakfast.sav dataset that we used for the class presentation (it can be found on the class portal under course materials). Create a histogram of the frequency distribution for the poptart variable (analyze/descriptive statistics/frequencies). Move poptart to the variable box. Be sure to ...
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and 1

Powerpoint
Powerpoint

... Tranformations must be described in the Results section of your manuscript. Effects of transformations on the validity of your t or F statistical tests is unclear. Nonparametric tests may be preferable but make probability of Type II error greater. ...
Ch 12: Analysis of Quantitative Data
Ch 12: Analysis of Quantitative Data

General Psychology 1
General Psychology 1

7-2D: Sample Size required to estimate a population mean Examples
7-2D: Sample Size required to estimate a population mean Examples

... ©2013 Eitel ...
Exam 3 study guide
Exam 3 study guide

Square Roots Print Activity
Square Roots Print Activity

hsm11a2ep_041
hsm11a2ep_041

... 14. To mark its eighth anniversary, Pizzeria Otto has a special coupon that offers the same price on a pizza with any combination of the 8 original toppings. Each pizza must have at least one topping. How many different kinds of pizza can be ordered with the ...
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STA 291-021 Summer 2007

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Slides - dollar

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Lecture2

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STATISTICS 2 Summary Notes

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Frequency Distribution

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Math 140 Confidence Intervals #7 Constructing Confidence Intervals

... and 1 population proportion (percentage) Confidence intervals give two values that we think the population value is in between. To construct a confidence interval, we start with the sample value (point estimate) and then add and subtract a certain number of standard deviations from the sample value. ...
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Solution

Practice Exam Final KEY - Department of Statistics, Purdue University
Practice Exam Final KEY - Department of Statistics, Purdue University

... had never smoked regularly at any point in their lives. The researchers found a higher proportion of cancer cases among those who had smoked regularly than among those who had never smoked regularly. What type of study is this? a) An experiment but not a double-blind experiment b) A double-blind exp ...
Lab 3 – Binomial Distribution
Lab 3 – Binomial Distribution

Hypothesis Test Summary
Hypothesis Test Summary

... The null hypothesis tells us what value the parameter has, and therefore tells us something about what value we should see for our test statistic. Of course, because the test statistic is a random number, we probably won’t see exactly the value the null hypothesis says we should, even if the null hy ...
Lecture 9 - Statistics
Lecture 9 - Statistics

...  Last day, introduced a point estimator…a statistic that estimates a population parameter  Often more desirable to present a plausible range for the parameter, based on the data  We will call this a confidence interval ...
Statistical Analysis (Word)
Statistical Analysis (Word)

Data Summary and Visualization
Data Summary and Visualization

< 1 ... 174 175 176 177 178 179 180 181 182 ... 285 >

Misuse of statistics

Statistics are supposed to make something easier to understand but when used in a misleading fashion can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.
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