Last Updated 22 Jun 2020

# Ftm 460 Exam3 Study Guide

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FTM 460 Exam 3 Review (Chapters 10-13) 33 Multiple Choice Questions (3 points each). The majority of test questions come from Chapter 10 & Chapter 13. The least from Chapter 11. Chapter 10: The concept of measurement * Be able to recognize the 4 types of measurement scales: CHART 10. 4 in chapter ten slide six * Nominal: Scales that partition data into mutually exclusive and collectively exhaustive categories. Ordinal: Scales that maintain the labeling characteristics of nominal scales and have the ability to order data * Interval: Scales that have the characteristics of ordinal scales, plus equal intervals between points to show relative amounts; they may include an arbitrary zero point. * Ratio: Scales that have characteristics of interval scales, plus a meaningful zero point so that magnitudes can be compared arithmetically. * Define: Scale reliability: Degree to which measures are free from random error and, therefore, provide consistent data.

The extent to which the survey responses are internally consistent. Cronbach’s alpha: Test-retest reliability: The ability of the same instrument to produce consistent results when used a second time under conditions as similar as possible to the original conditions. * Be familiar with the steps in the measurement development process (McDaniel’s diagram) Slide 3 CH 10. * Know the difference between a constitutive and operational definition of a given construct. Slide 4) * Constitutive: ambiguity is a direct function of the discrepancy between the information available to the person and that which is required for adequate performance of a role. It is the difference between a person’s actual state of knowledge and the knowledge that provides adequate satisfaction of that person’s personal needs and values. * Operational: Role ambiguity is the amount of uncertainty (ranging from very uncertain to very certain on a five-point scale) an individual feels regarding job role responsibilities and expectations from other employees and customers. Be able to distinguish between convergent vs. discriminant validity. * Convergent: The degree of correlation among different measures that purport to measure the same construct. * Discriminate: The measure of the lack of association among constructs that are supposed to be different. Chapter 11: Using measurement scales to build marketing effectiveness * Define: Semantic differential scale (10) , Likert scale--be able to recognize examples of each (12) Agree, Somewhat Agree, Somewhat disagree, Disagree.

Chapter 12: Questionnaire design * Know the differences between the following types of question formats: * open-ended: Questions to which the respondent replies in his or her own words. * Probed vs Un-probed * closed-ended: Questions requiring respondents to choose from a list of answers * Dichotomous: Choice between two answers * Multiple Choice * Scaled Responses * What are the reasons for using screening: to identify qualifies respondents and probing questions?

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When do we use branching? * Understand sequencing rules for laying out questions in a survey (i. e. , general questions first). Slide 16 * Screeners, Warm-up (Easy to answer questions show the respondent that the survey is simple), Transitions (Questions related to research objectives require slightly more effort), Difficult Complicated (The respondents has committed to completing the questionnaire), Classifying and demographic. Chapter 13: Basic sampling issues * Know the difference between a Probability: Everyone in the population has a known, nonzero, likelihood of selection (Simple random, Systematic, Stratified, Cluster) * Non-probability: Samples in which specific elements from the population have been selected in a nonrandom manner. (Convenience, Snowball, Judgment, Quota) * Know the difference between a sample and a population. (Population is the entire group of people about whom information needed; also called the universe or population of interest. ) * Define: simple random sample: A sample selected by assigning a number to every element of the population and then using some method for randomly selecting elements to be in the sample such as random digit dialing * systematic random sample: A sample in which the entire population is numbered and elements are selected using a skip interval (every Nth name is selected * stratified random sample: A sample that is forced to be more representative through simple random sampling of mutually exclusive and exhaustive subsets either proportionally or disproportionally.

Good for data that are not normally distributed. * Convenience sample: A sample based on using people who are easily accessible – such as mall intercepts or other high traffic locations. * Sampling error: Error that occurs because the sample selected is not perfectly representative of the population. * Be familiar with the McDaniel’s stages of a sampling plan * Define the target Population- Determine the characteristics of those you are interested in studying.

Determine which group of people or entities about which you want to learn more. * Choose the Data Collection Method- Determine how you collect the sample – such as mail, Internet, telephone, mall intercept, ect. * Select the Sample Frame- A list of population elements from which units to be sampled can be selected. * Obtain the Sample- Determine how you will get the sample list through probability or non-probability methods. * Determine Sample Size * Select Sample Units * Conduct Fieldwork

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