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02b
02b

... data cube  A data cube is a multidimensional representation of data, together with all possible aggregates.  For example, if we choose the species type dimension of the Iris data and sum over all other dimensions, the result will be a one-dimensional entry with three entries, each of which gives t ...
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Monte Carlo Simulation Basics

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Comparing two groups - Part 1 - Garvan Institute of Medical Research

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What is a Two-Sample Test - McGraw Hill Higher Education

... Comparing Two Proportions Testing for Zero Difference: 1 = 2 ...
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7.3 Estimating a Population Mean

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Measures of Position

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Review for Test 3 F09 Solution

... rate at each. The sample mean rate is 6.93% with a sample standard deviation of 0.42%. Find the 99% confidence interval for the population mean mortgage interest rate. Assume the interest rates are approximately normally distributed. Since the population standard deviation, σ, is unknown, and n < 30 ...
Classroom Voting Questions: Elementary Statistics
Classroom Voting Questions: Elementary Statistics

... 33. The ACT has a mean of 21 and an SD of 5. The SAT has a mean of 1000 and a SD of 200. Joe Bob Keith took the ACT and he needs a score of 1300 on the SAT to get into UNC-Chapel Hill and a score of 1400 on the SAT to get into Duke. UNC and Duke both told Joe Bob Keith that they will convert the AC ...
Sampling Distribution of the Mean
Sampling Distribution of the Mean

... The COE’s mean GRE score of the 565, and the standard deviation equals 75, and there are 300 students in the COE. Our degrees of freedom equals 299 for this test (df=300-1). Looking at the column in the t table on p.682 with the “Level of Significance for One-Tailed Test” equals 0.05 and the df equa ...
AP Statistics Chapter 23
AP Statistics Chapter 23

... Nearly Normal Condition • For very small sample size (n<15), the data should follow Normal model pretty closely. If you find outliers or strong skewness don’t use tmodel. • For moderate sample sizes (15
the take-home section of next week`s exam
the take-home section of next week`s exam

... points). In each section state clearly what number you are using to personalize data. There is a penalty for failing to include your student number on this page, not clarifying version number in each section and not including class hour somewhere. Please write on only one side of the paper. Be prepa ...
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analysis of variance and experimental design

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Power Point Slides for W&W, Chapter 6

Inferential Statistics Statistical inference is the branch of statistics
Inferential Statistics Statistical inference is the branch of statistics

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Physics 509: Non-Parametric Statistics and Correlation Testing

introduction to statistics - nov 2012
introduction to statistics - nov 2012

... Please write your examination number on each answer book used. Answer sheets without examination numbers will not be marked. ...
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Methods for Describing Data I. Describing Qualitative Data (i

... SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. 7) Parking at a large university has become a very big problem. University administrators are interested in determining the average parking time (e.g. the time it takes a student to find a parking spot ...
confidence interval
confidence interval

Statistical Reasoning
Statistical Reasoning

... continuously getting larger.) the bars touch, because you have to have a class for each score to fall into, and you can’t have any “gaps.” Different than a Bar Graph which is used when you have non-continuous classes (example, which candidate do you support, Obama or McCain? You’d have a bar for eac ...
Descriptive Statistics
Descriptive Statistics

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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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