Class Notes (1,100,000)
CA (630,000)
U of G (30,000)
SOAN (900)
SOAN 2120 (400)
Lecture 10

SOAN 2120 Lecture Notes - Lecture 10: Sampling Distribution, Sample Size Determination, Microsoft Powerpoint


Department
Sociology and Anthropology
Course Code
SOAN 2120
Professor
David Walters
Lecture
10

This preview shows page 1. to view the full 5 pages of the document.
SOAN 2120 Introductory Methods October 3rd, 2017
Read Chapter 5
Chapter 5
NVivo 11 a qualitative software program that is designed to facilitate qualitative research
o This software consolidates and collates the various data sources that a researcher may
have by electronically organizing them and allowing for retrieval of items from locations
Theory emerges from the research process rather than being the central
framework that informs and directs the research project from the beginning
The employment of qualitative software should never substitute a deep personal understanding
NVIVO Program
o Sources contains the data sources that you import into your projects
Internals
You can create subfolders to organize your material in
Externals
Contain references and links to source material that cannot be directly
imported into your project (ex: hardcopy books, webpages, PowerPoint)
Memos
A site where you can note your reflections, thoughts, ideas, questions
Nodes a receptacle for all references to a particular theme or concept
o Picture it as a box with thematic label: each time you code something into a theme
NVivo enhances the eseahe’s ability to organize, link and ask questions of the data with goals
Concerns with NVivo
o Computer-assisted research remains true to the spirit of qualitative methods
o Use of such software leads to a greater separation between data/investigator
o Loss of contextualizing detail when field notes or media sources are used
These concerns are countered by developments in the program (ex: memos/annotations)
The coding process is dependent on the analyst knowing and understanding their subject
In Class Lecture
0.5 and 0.1 are the key thresholds/values
o 1-.95 = 1/20 = 0.5 (lie between the inner most bars)
find more resources at oneclass.com
find more resources at oneclass.com
You're Reading a Preview

Unlock to view full version

Only page 1 are available for preview. Some parts have been intentionally blurred.

o 1-.99 = 1/100 = .01 (lie outside the outer most bars)
Which cut-off is better
o 0.5 or .01 neither is better or worse than the other (read textbook)
Just as variables have distributions, sample statistics have distribution as well
Calculating P-Values
Statistics Table show the values of the distribution functions for different parameters
o How do we know that a z-score of plus or minus 2 translates to p-value of 0.5?
They used calculus to figure it out how to calculate them by using integrals in university
Statistical Inference
If e ife soethig it eas that e da a olusio fo it
Using sample information to estimate the population values (p)
A tool for drawing conclusions from that are from a random sample
Probability allows us to take chance variation into account at times
If e do’t use ado saple, ou olusios a e halleged
There is absolutely no substitute for collecting good data whatsoever
Types of Distribution
Sample Distribution - the distribution of a variable using data from our random sample
o The example shown at the beginning of class related to height or grades
Population Distribution - the distribution of the variable in the population
o We typically do not see this; it is the same as the sample but it is estimated
Sampling Distribution - the distribution of the mean of the variable
from all possible samples of the same size from the same population
o This is generally the most difficult to understand for most people b/c its abstract
o It is theoretical, you cannot see it but we will look at theories and such to understand
o A sampling distribution is the theoretical distribution of a statistic from all possible
samples of the same size and the same population different sampling distribution/size
o Its standard deviation gets smaller as the size of the sample tends to get larger
Logic of Statistical Inference Repeated Sampling
What ould happe if e took a saples?
o Take a large number of samples from the same population
o Calculate the same statistics for each and make a histogram
o Resulting distribution will approximate the sampling distribution
It is a distribution of the means from all possible samples
The Mean of the Distribution of Samples is the Same as the Population Mean?
Statistical Theory
Stimulations
o Take a sample (income of 40,000 people)
Population
Calculate the mean 1000 random samples, then calculate the mean
of all of the sample means around the mean of the population, then
calculate the mean of the sample means and it will equal the true
population parameter which was previously unknown in the sample
find more resources at oneclass.com
find more resources at oneclass.com
You're Reading a Preview

Unlock to view full version