Jada Hardy & Malakai Miller Chapter 12 Jada Hardy & Malakai Miller

1. Examine Part of the Whole Population: A group of individuals Sample: Smaller group of individuals selected from the population Sample Surveys: surveys designed to ask questions of a small group of people in the hope of learning something about the entire population Biased: Bias is systematic favoritism that is present in the data collection process, resulting in lopsided, misleading results.

Sample v. Population

Bias Sampling methods that, by their nature, tend to over- or under- emphasize some characteristics of the population. There is usually no way to fix a biased sample and no way to salvage useful information from it. The best way to avoid bias is to select individuals for the sample at random

2. Randomizing Randomizing: Selecting people at random. It protects us from the influences of all the features of our population, even ones that we may not have thought about. It does that by making sure that on average the sample looks like the rest of the population. Randomizing protects us from bias, it actually makes it possible for us to draw assumptions about the population when we see only a sample

3. It’s the Sample Size

Does a Census Make Sense? Census: Sampling the entire population is a census. There are problems with taking a census: It can be difficult to complete a census—there always seem to be some individuals who are hard to locate or hard to measure ; or it may be impractical- food. Populations rarely stand still. Even if you could take a census, the population changes, so it’s never possible to get a perfect measure.

Populations & Parameters

Simple Random Samples Representative: A sample that reflects the corresponding parameters accurately. Simple Random Sample: A method where each combination of people has an equal chance of being selected. Sampling frame: A list of individuals from which the sample is drawn.

Notation

Simple Random Samples Simple Random Sample (SRS)– Each person and combination of people have an equally likely chance of being selected.

Stratified Random Sampling

Cluster Sampling

Multistage Samples

Systematic Sampling

Convenience Sample Examples:

Who’s

Things to remember…

What Else Can Go Wrong? Work hard to avoid influencing responses. Response bias refers to anything in the survey design that influences the responses. For example, the wording of a question can influence the responses

Here’s a Video http://www.youtube.com/watch?v=BKCU3SJXig8&edufilter=Db24N54Eu_vpe4P65Iz5Fa&safe=active