Class Notes (837,186)
Canada (510,155)
Criminology (2,192)
CRIM 320 (64)
Lecture 4

Crim 320 - week 4.docx

3 Pages
82 Views
Unlock Document

Department
Criminology
Course
CRIM 320
Professor
Rebecca Carleton
Semester
Winter

Description
Crim 320 – week 4 – Distributions, the Normal Curve, and Hypothesis Testing Housekeeping: - Outline has been revised - Office hours have been revised: please feel free to go to any or all - All assignments will be handed in during lecture - Must have both names, both std numbers, and tutorial in which it will be picked-up Objectives - Discuss the fundamentals of the binomial distribution - Explain how sample size affects statistical significance - Explain how hypothesis testing and testing and tests of statistical significance are related to the standard normal distribution. - Sample has stats - When we can make inferences from sample |stats to a population| parameter, it’s significant if it has an effect, real results Hypothesis Testing - Hypothesis testing is about evaluating sample results. It focuses on two closely related questions - What can we say about a population based on the results observed in a sample? - Are the sample results identical to the results we would observe from the entire population? The binomial distribution - Is relevant for variables that can only have two possible outcomes - Ex. For example, flipping a coin. Would expect % heads but might not - How often would we get a result that differed from our expectation of five? - A binomial distribution is a dist that can only have two possible outcomes Ex: Flip a coin Sampling dist – a distribution of all possible sample outcomes for a statistic Standard error – the standard deviation of a sampling distribution Ex: Recidivism - First, select 10 parolees at random, and count number of times they “succeed” within five years of release. Then, repeat this process 500 times. - See graph. Add from “Number of Trials” colum: 66 + 24 + 4 _ 2 = 96/500= 19.2% How Unusual? - In the social sciences, we tend to use the 5 percent rule - If the chance of a given outcome is less than five in 100, we say that it is unusual - A claim of statistical significance suggests that the result would happen in fewer than 5 percent of trials - Something actual is going on The effects of Sample size – n=10 - LESS than 0.05, results are statistically significant - GREATER than 0.05, results are not statistically significant - Since 0.344 is greater than 0.05, the results are not significant. - If Greater, then possibly due to chance The effects of Sample size – n=40 - All that has changed is the sample size - But the impact of
More Less

Related notes for CRIM 320

Log In


OR

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


OR

By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.


Submit