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Stats handouts
Stats handouts

... Type of Statistical Test to Use • Continuous variable as end point – 2 groups: t-test – 3 or more groups: ANOVA • Relation between 2 categorical variables: ...
Descriptive Statistics
Descriptive Statistics

Guided5 200 ans - Ilvento Web page
Guided5 200 ans - Ilvento Web page

Quarter 2 Exam Review Sheet:
Quarter 2 Exam Review Sheet:

... a) Sample Mean = _____ b) Standard Deviation = _____ c) Use Chebyshev’s Theorem to find an interval centered about the mean in which you would expect 93.8% of the data to fall. d) Use Chebyshev’s Theorem to find an interval centered about the mean in which you would expect 99% of the data to fall. e ...
Chapter 10 Test Review
Chapter 10 Test Review

Oct 2008 - UBC Zoology
Oct 2008 - UBC Zoology

... Fisher's exact test (because the expected values of one of the cells are too low to use the χ2 test.) H0: Survival and drug treatment are independent. 4. We are often happy to do favors for other people when they have a particular need. For example, we are more willing to let someone use a photocopi ...
Introduction-to-Statistics
Introduction-to-Statistics

Activity 3.7 Statistical Analysis with Excel (PREVIEW)
Activity 3.7 Statistical Analysis with Excel (PREVIEW)

Stats-for-abbvie-biopharm-lecture
Stats-for-abbvie-biopharm-lecture

Final
Final

... oranges and find out what they tell us about the population of all bags in this shipment. We are only interested in whether or not the bags are underweight, so each bag is weighed and counted as underweight if it weighs less than 5 pounds. Five bags in our sample of 100 were found to be underweight. ...
Sample size and power lab (DRAFT)
Sample size and power lab (DRAFT)

Stat 280 Lab 9: Hypothesis Testing
Stat 280 Lab 9: Hypothesis Testing

11.1
11.1

Introduction to Biostatistics
Introduction to Biostatistics

... (This is not the statistically correct interpretation, but it relatively easy to understand as such, and this interpretation is commonly used.)  Probabilistic interpretation: in repeated random sample of the population, 95% of all such intervals will, in the long run, contain the true population me ...
Chapter 20: Inference about a Population Mean Two most common
Chapter 20: Inference about a Population Mean Two most common

day2
day2

Solution
Solution

... deviation σ = 0.1 milligrams. The brand advertises that the mean nicotine content of their cigarettes is µ = 1.5. The FDA believes that the actual nicotine content is higher than what is advertised by the brand, and they plan to investigate the advertised claim by measuring the nicotine content of 1 ...
Chapter 3 Slides
Chapter 3 Slides

... for random digits • Replication: Apply treatments to as many units as possible • Statistical Significance: Observed effect that exceeds what could be expected by chance ...
Stats & Correlation
Stats & Correlation

... • The Wechsler IQ scale • Range- gap between high and low scores • Standard deviation- measures the degree to which scores deviate from one another • EX: IQ ...
STA 2023 - FAU Math
STA 2023 - FAU Math

IB Math SL Chapter 20F
IB Math SL Chapter 20F

... edit 1, clear L1 by moving curser on top of L1 and hit clear enter, enter data, 2nd quit. ...
Suppose that as a military psychologist you know that the population
Suppose that as a military psychologist you know that the population

10.3 Statistical Significance
10.3 Statistical Significance

Lecture 12. Estimation of authenticity of statistical research
Lecture 12. Estimation of authenticity of statistical research

Practice Test 1
Practice Test 1

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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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