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Confidence Intervals
Confidence Intervals

... error known as the probable error. For example, an estimate x-bar of the average useful life of a TV picture tube is said to have a probable error of e years if there is a 50% chance that the interval from x-bar – e to x-bar + e has a 50% chance of including the population mean. Calculate the probab ...
Populations and Samples
Populations and Samples

L00D MGS8110 Statist.. - Georgia State University
L00D MGS8110 Statist.. - Georgia State University

Hypothesis Testing Using z- and t-tests In hypothesis testing, one
Hypothesis Testing Using z- and t-tests In hypothesis testing, one

Chapter 1
Chapter 1

... *Classes always represent a variable, non-overlapping; each value is belong to one and only one class. The numbers listed in second column are called frequencies, which gives the number of values that belong to different classes. Frequencies denoted by f. Table 1.2 : Weight of 100 male students in X ...
Review of basic statistics and the mean model for
Review of basic statistics and the mean model for

... The mean is not the only statistic for measuring a “typical” or “representative” value drawn from a given population. For example, the median (50th %-tile) is another summary statistic that describes a representative member of a population. If the distribution is symmetric (as in the case of a norma ...
foreign exchange rates
foreign exchange rates

Here - School of Mathematical and Computer Sciences - Heriot
Here - School of Mathematical and Computer Sciences - Heriot

A note on detecting statistical outliers in psychophysical data
A note on detecting statistical outliers in psychophysical data

5 GOODNESS OF FIT TESTS
5 GOODNESS OF FIT TESTS

Research and Data Analysis
Research and Data Analysis

Confidence Intervals for the mean
Confidence Intervals for the mean

Chapter 11 Practice Exam
Chapter 11 Practice Exam

1. The hindsight bias refers to people`s tendency to: A) dismiss the
1. The hindsight bias refers to people`s tendency to: A) dismiss the

... 39. Psychologists select a random sample of research participants in order to ensure that: A) the participants are representative of the population they are interested in studying. B) there will be a large number of participants in the research study. C) the study will not be influenced by the resea ...
Sample Homework 4
Sample Homework 4

The SURVEYMEANS Procedure Statistical Computations The
The SURVEYMEANS Procedure Statistical Computations The

Topic - University of Oklahoma
Topic - University of Oklahoma

... Note: (E), (F), and (G) are all included as options so that students are less able to answer correctly without actually understanding what the correct answer is. (A) A parameter is typically indicated with a letter from the Greek alphabet (such as  for a population mean) and a statistic is typicall ...
Annotated Clicker Questions
Annotated Clicker Questions

random sample
random sample

• Two basic types of statistics: 1. Descriptive stats – methods for organizing and summarizing  information
• Two basic types of statistics: 1. Descriptive stats – methods for organizing and summarizing  information

Exploring Data With Base SAS® Software
Exploring Data With Base SAS® Software

CHAPTER 1
CHAPTER 1

here
here

... and have no chance of being selected  Non response error or bias  People who do not respond may be different from those who do respond  Sampling error  Chance (luck of the draw) variation from sample to sample.  Measurement error  Due to weaknesses in question design, respondent error, and int ...
Sample
Sample

FITTING DISTRIBUTIONS WITH R
FITTING DISTRIBUTIONS WITH R

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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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