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82 Cards in this Set
- Front
- Back
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Nominal
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Purpose:
Classification Ex. Team player #'s |
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Ordinal
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Purpose:
Rank order Ex. 1st, 2nd, 3rd |
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Interval
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Purpose:
Measuring differences Arbitrary zero Ex. Temperature |
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Ratio
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Purpose:
Comparison of absolute magnitudes Zero is not arbitrary Ex. Profit |
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Three properties of the numberying system
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P1: Follow a specific order 9>3
P2: The difference between pairs of number can be compared Ex. 6-3=9-6 P3:We can divide one number by another and interpret the resulting ratio. Ex. 6 is twice as large as 3. |
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Applicable number properties for Nominal
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None
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Applicable number properties for Ordinal
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P1: Rank order
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Applicable number properties for Interval
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P1: Rank order
P2: Difference between pairs is measurable |
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Applicable number properties for Ratio
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P1: Rank order
P2: Difference between pairs is measurable P3: Two measurments can be compared. |
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What are the central tendencies?
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Mean: Average
Median: Middle value Mode: What occured the most |
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What are applicable statistical tests for Nominal?
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Chi-Squared
Percentages |
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What are the applicable statistical tests for Ordinal?
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Chi-Squared
Percentages |
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What are the applicable statistical tests for Inverval?
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Correlation Tests
ANOVA Regression |
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What are the applicable statistical tests for Ratio?
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Correlation Tests
ANOVA Regression |
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Comparitive scales
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A judgment comparing one object, concept, or person against another
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Paired Comparison Scales
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(Comparitive) Respondents are given objects two at a time and asked to select which one they prefer.
Number of comparisons: n(n-1)/2 |
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Rank Order Scales
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(Comparitive) Respondents compares one item with another and ranks them.
Problem: don't know amount by which one is preferred over another |
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Constant Sum Scale
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(Comparitive) Respondents are allocated a fixed number and asked to allot points based on relative importance totalling to that amount to each object.
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Pictoral Scale
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(Non-comparitive) Categories are shown graphically. Good for children and illiterate.
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Continuous (Graphical scale)
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(Non-comparitive) Rate objects by placing a mark in the appropriate position on a line running from one extreme to another.
Problem: hard to quanitify, use of decimals |
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Likert Scale
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(Non-comparitive) Respondents indicate thier own attitudes by checking how strongly they agree or disagree with statements.
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Semantic Differential
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(Non-comparitive) A series of seven-point rating scales with bi-polar adjuectives, such as good/bad, achore the ends. Weight is assigned to each position.
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Stapel Scale
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Use of a single adjective for the semantic differential when it is difficult to create pairs of bipolar adjectives.
-1-2-3<Wide selection>1 2 3 |
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Image Profile
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A graphical representation of semantic differential data for comparing brands, products or stores to highlight comparisons.
Stack semantic differentials and compare mean or median. |
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Five issues that need to be addressed when designing a survey
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1) Extent of category description
2) Number or response options 3) Treatment of respondent uncertainty or ignorance 4) Balance favorable and unfavorable categories 5) Strength of anchors |
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Why is questionnaire design one of the most critical stages in survey and causal research?
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It is one of the most critical stages because a survey is only as good as the design. Bad questions=bad results=bad decisions
Questions must be relevant and accurate |
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What questions must be answered when designing a survey?
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1) What should be asked? (Relevency)
2) How to phrase? (Accuracy) 3) What sequence? 4) What layout? 5) How to pretest? |
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Open ended questions
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Unstructured
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Closed ended/ fixed-alternative questions
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Structured:
Multiple choice Dichotomous Scales |
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Seven mistakes of questionnaires
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1) Complex language
2) Ambigous language 3) Leading questions 4) Double barreled questions 5) Making assumptions 6) Burdensome questions 7) Long questions |
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What three criteria should you ensure that your response categories meet?
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1) Responce categories are relevent
2) Responce categories are exhaustive 3) Responce categories are mutually exclusive |
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How should you sequence questions?
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Filter questions: screen out those who aren't qualified
Sensitive questions: put them toward the end Funnel: ask general before specific |
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What overall order should questionnaires follow?
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1) Qualify/ Screening
2) Introductory questions/warm ups 3) Main questions (easy) 4) Main questions (more difficult) 5) Psychographics/lifestyle 6) Demographics 7) Indentification info |
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Pretesting
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Testing a questionnaire on a small sample of respondents to identify and eliminate potential problems.
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Experiment
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A carefully controlled study in which the researcher manipulates a proposed cause and observes any corresponding change in proposed effect.
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Experimental Variable (Indenpendent variable)
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Respresents the proposed cause and is controlled by the researcher by manipulating it
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Manipulation
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The researcher alters the level of the variable in specific increments.
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Dependent Variable
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The effect (outcomes of interest) that are hypothesized to be influenced by the independent variable
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Pre-experimental designs do not include:
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Ransom assignment
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What characteristic do True experimental designs have that pre experimental designs do not?
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Such designs involve random assignment of participants to treatments.
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Statistical designs
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Such designs allow you to 1) examine the effects of different levels of an independent variable and 2) two or more indenpendent variables.
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Types of pre-experimental designs
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One-shot/After-only
One group Pre-test/Post-test Time series Control Group Design |
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Types of True experimental desins
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After-Only
Pre-test/post-test Solomon Four Group design |
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Types of statistical designs
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Completly Randomized Block
Randomized Block Design Factorial Design |
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What are validity threats to One-shot/After Only Design?
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History and Maturation
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What are validity threats to One group pre-test post-test?
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History and Maturation
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What validity threat applys to all Pre-experimental designs?
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Selection bias
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How does time-series design address problems with pre-test/post-test design?
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Addresses problems with history and maturation by taking several measures over time, both before and after period of interest.
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How does control group design address problems with the other pre-experimental designs?
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Address problems with history and maturation by including a control group. Helps identify any variables that may also be affecting dependent variable.
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Internal validity
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Reflects the accuracy of the measurement
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What are the threats to internal validity?
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History
Maturation Selection bias Mortality Testing |
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History
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Change in events between the beginning and end of the experiement that may influence the dependent variable
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Maturation
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Change in subjects during the course of study that effects the responce to the indenpendent variable
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Selection bias
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Not having randomly assigned groups
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Solution to threats to internal validity
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Use true experimental designs. There is less threat to internal validity but realism is sacrificed.
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External validity
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Reflects the generalizability of the experiment beyond the experimental situation. "Realism"
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Threats to external validity
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Artificiality of measures
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Lab Experiements
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Artificial settings
Isolates research under controlled conditions Short duration Less costly than field experiements Less external validity |
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Field Experiments
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Completely natural environment
Less control over conditions Long duration More expensive than lab experiments Greater external validity |
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Sampling errors
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Population errors
Non-responce errors |
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Non-sampling errors
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Ambiguity of questions
Interviewer error Ambiguity of answers Inaccuracy in response |
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Population
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Any complete group of entities that share a same common set of characteristics
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Census
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An investigation of all the individual elements that make up a population
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Sample
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A subset, or some part, of a larger population
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Population element
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An individual member of a population
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Sample frame
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A list of elements from which a sample may be drawn
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Non-probability sampling methods
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Convenience sampling
Snowball sampling Quota samling |
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Probability sampling
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Simple Random Sample
Systematic Sampling Proportional Stratified Sampling Cluster Sampling |
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Convenience sampling
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Obtaining those people or units that are most conveniently available to the researcher
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Snowball sampling
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Initial respondents are selected by probability methods and additional respondants are obtained from information provided by the initial responses.
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Quota sampling
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Ensures that various subgroups of a population will be represented on pertinent characteristics to the extent that the investigator desires
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Simple Random sampling
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Assures each element in the population has a known and equal chance of being included in the sample
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Systematic Sampling
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Order all units in the sampling frame and number them from 1 to N. Choose a random starting place from 1 to k and then sample every kth number after that. Let k=N/n
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Proportional Stratified Sampling
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The population is divided into subgroups (or strata) and then elements within each stratum are drawn in proportion ot the population size of that stratum.
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Cluster Sampling
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Population is divided in subgroups (or clusters) and clusters (not individual elements) are selected at random and all members of a subgroup are measured.
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What one requirement is there for the chi-square statistic (hint: it concerns the expected frequencies)?
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Expected frequencies must be at least 5
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One Sample t-test
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Used when comparing a sample mean to a specific value
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Paired Sample t-test
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Used when comparing means from one group on two different items
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Independent Samples t-test
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Used when comparing means from two groups on a single item
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Hypothesis testing
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The method used to prove or support arguments with statistics
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Alternative hypothesis
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What you are trying to prove, the new idea
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Null hypothesis
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The opposite of the alternative hypothesis
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