INFO 370 - L06 - October 18, 2004 Notes By: Prins, Fortier, Egaas Format: UTF-8 Retarded ASCII time!! Left Skewed (Negative) _____| __/ | __/ | _/___________| Right Skewed (Positive) |____ | \___ | \___ |____________\ saxton iddn't massage the data heheehehhe 1 yes 2 no 3 don't know 4 SYSMISSING NEW SHIT 1 Yes 2 No = 0 3 No = 0 9 SYSMISSING SYSMISSING No Frequency Chart (on green handout) Internet Poll -- Cheap -- Low Response Rate Telephone Poll -- Expensive -- Highest Response Rate In-Person -- Expensive -- Highest Response Rate Confidence Intervals (Confidence level = z score) 99% -> need to be sure - critical medical studies (p: .005, z: 2.576) 95% -> Kinda need to be sure (p: .025, z: 1.960) 90% -> less sure (p: .05, z: 1.645) --Unicode text below-- n = ((z*σ)/m)² --- Sample size desired for margin of error Quiz on Wednesday Descriptive versus Experimental Study > Descriptive * To find out characteristics of the populations * Snapshot of the population * Does not always have a hypothesis > Experimental * Cause and Effect * Explanatory * Predictive * Impose certain controls (Explicitly defined variables) * ALWAYS HAS A HYPOTHESES Exploratory verses Descriptive > Exploratory * No Hypothesis * Open ended questions * Definition of variables usually come while doing the study * Study something in its natural setting with few or no preconceived ideas What makes things forms of evaluation > Has to be something in place > Set standards for which you judge outcome, an evaluation Review definitions for levels of measurements > Nominal > Ordinal * Categories could be evenly spaced * Doesn't make sense to talk about 0.5, 0.4 (no numerical relationship) > Ration > Interval * No absolute zero * Even interval (numerical relationship) Participant and Non-Participant Observation > Participant * Watched them watching TV and their habits > Non-Participant * Asking them about how they watch TV and their habits Format > Given various situations then you answer them > Multiple Choice > Check all of the slides SAMPLING Population Population: A group of people or objetcts you are interest in studying Sample: A subset of the total population Unit: An individual member of the population (case, subject respondent) Sampling Sampling: The process of selecting units for observation Sampling Frame: Source from which the selection was made (e.g., a list) Variable: A characteristic of a unit Observation: Noting the value of a variable for a given unit Sampling Error > Any difference between the characteristics of a sample and the characteristics of the population from which it was drawn. Identify the Population > Define the population concretely > Examples: - Adult residents of Seattle - Official homepages produced by community colleges in the United States - Phone calls received at the technical support service desk for a software company Census vs. Sample > Cencus - Observe each unit - An "attempt" to observe the entire population > Sample - Observer a sub-group of the population Types of Sampling Methods > Probability (random) > non-probability (non-random) Random Sampling > Objective > Each unit (element) has the same change (probability) of being picked) > Change determines who is in the sample Types of random sampling (KNOW THESE) > Simple random sample (SRS) > Systematic sampling > Stratified sampling > Cluster sampling Simple Random Samples 1) Obtain a complete sampling frame 2) Give each unit a unique number 3) Decide on the required sample size 4) Select that many numbers from a table of random numbers 5) Select the units which correspond to the randomly chosen numbers Systematic Sampling > Sample fraction - divide population y the desired sample size > Select from the sampling frame according to the sampling fraction - e.g. sample faction = 1/5 means that we select one person for every five in the population > Starting point - First unit (random first place to start) - Random Stratified Sampling > Premise - if a sample is to be representative then proportions for various groups in the sample should be the same as in the population > Stratifying variable - characteristic on which we want to ensure correct representation in the sample > Order sampling frame into groups Cluster Sampling > Involves drawing several different samples > Draw a sample of areas > Start with large areas then progressively sample smaller ares within the larger - Divide city in districts - select SRS sample of districts - Divide sample of districts into blocks - select STS sample of blocks - Draw list of households in each block - select SRS sample fo households Benefits > Minimizes bias of investigator > High probability that sample generally representative of the population on variable of interest > Ability to generalize from sample to population using statistical techniques Non-Random Samples > Availability > Quota > Purposive > Snowball Availability Sampling > When we study only cases that are available to us > Examples: - Surveys by TV station - Running an experiment with students in your university - Interviewing kids whose parents gave permission > When? - Exploratory research Quota Sampling > Representation is established at levels defined by the investigator > Selecting cases though availibility sampling or random sampling > NOT PROPORTIONAL Purposive Sample > Each single case is selected for a purpose, because of the unique position it has. > Examples: - Top 5% of students in the department - Bottom 5% of students in the department - Most popular search engines - Web browser with highest market share Snowball Sampling > One identifies one person in the population and ask her or him to identify additional people, and so on. > Examples: - Members in an online community - Participants in a secret and exclusive listserv - Members of the same professional organization # END #