# CCJS 300 Lecture Notes - Lecture 7: Central Limit Theorem, Null Hypothesis, Chi-Squared Distribution

by OC2395438

School

University of MarylandDepartment

Criminology and Criminal JusticeCourse Code

CCJS 300Professor

Alan LehmanLecture

7This

**preview**shows half of the first page. to view the full**1 pages of the document.**STATISTICS & DATA ANALYSIS

-Each step of hypothesis testing

-CCJS is a science, statistics is a tool we use to answer our questions

DESCRIPTIVE AND INFERENTIAL RESEARCH

-Explanatory research

-Language & vocabulary

-Theories, hypotheses, validity, causality

-Sampling

-Independent & dependent variables

-Levels of measurement (nominal, ordinal-order the responses, interval-equal intervals

between, ratio- true zero point)

-Measures of central tendency:

-Mode: most frequently seen actual number

-Median: middle value in a set of data, the 50th percentile

-Mean: the average of a set of data (subject to influence by outliers)

-Measures of dispersion (spreadoutness)

-VR: variation ratio, 1-(fmodal category/n)

-Range: Highest value-lowest value

-IQR: interquartile range, middle 50% of a distribution

-Variance: s2= (

)

-Standard deviation:

PROBABILITY AND PROBABILITY DISTRIBUTIONS

-1 trial vs “in the long run”

-Gambler’s fallacy

-Bounding rule 0<p<1

-Addition rules

-Multiplication rules

-Bell shaped standard normal curve, 50% on each side, unimodal, symmetric, theoretical,

asymptotic (never touches the x-axis)

Z SCORES

-Deviation from the mean while taking into account the standard deviation

-Going from raw scores to scores in its particular data

-Central limit theorem: we do not have to worry about the shape of the underlying population

distribution

-Sampling distributions are the link between samples and populations

STEPS IN HYPOTHESIS TESTING

-Associations, set up null and alternative hypotheses

-Appropriate statistic & its sampling distribution (i.e. t test, f test, chi square, correlation

regression, etc.)

-Set p value, alpha level (usually .05), critical value, rejection regions

-Calculations, performing the test

-Decision/Interpretation, reject or fail to reject the null hypothesis

-Rejection is good, this means finding is not the status quo, statistically significant

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