Study Guide Exam 3
Study Guide Exam 3 MKT 319
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This 9 page Study Guide was uploaded by Danielle Lynch on Thursday December 3, 2015. The Study Guide belongs to MKT 319 at Michigan State University taught by R. Spreng in Summer 2015. Since its upload, it has received 220 views. For similar materials see Marketing Research in Marketing at Michigan State University.
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Date Created: 12/03/15
Exam 3 Study Guide MKT 319, Fall 2015 Chapter 14 (Lecture) Methods of data collection • In-person Interview • Phone Interview • Mail • Online • Mobile Online Panels • A panel provider is a firm that provides a sample of opt-in respondents who are compensated to complete research. • Used by most marketing research firms and corporate clients o Some firms create their own panel Type of sampling • Non-probability sampling o Convenience sampling: Obtain a sample of convenient elements. The selection of sample units is left primarily to the interviewer. o Judgmental sampling: The population elements are purposively selected based on the judgment of the researcher o Quota sampling: A two-stage restricted judgmental sampling. The first stage consists of developing control categories or quotas of population elements. In the second stage sample elements are selected based on convenience or judgment o Snowball sampling: An initial group of respondents is selected randomly. Subsequent respondents are selected based on the referrals or information provided by the initial respondents. This process may be carried out in waves by obtaining referrals from referrals. • Probability sampling o Simple random sampling: Each element in the population has a known and equal probability of selection. Every element is selected independently of every other element, and the sample is drawn by a random procedure from a sampling frame. o Systematic sampling: Sample is chosen by selecting a r andom starting point and then picking every ith element in succession from the sampling frame o Stratified sampling: Two-step sampling process, producing a probability rather than a convenience or judgment sample ▯ Within a stratum, elements should be homogeneous with clear differences (heterogeneity) between the strata. o Cluster sampling: A two-step probability sampling technique. First, the target population is divided into mutually exclusive and collectively exhaustive subpopulations called clusters. Then, a random sample of clusters is selected based on probability sampling technique, such as simple random sampling. For each selected cluster, either all the elements are included in the sample or a sample of elements is drawn probabilitistically ▯ Within a cluster, elements should be different (heterogeneous) whereas homogeneity or similarity is maintained between clusters Advantages Less social desirability “Survey walls” which draw people to taking surveys Disadvantages/problems/concerns Problems 1. Respondent Quality a. False identities b. Fraudulent qualifying c. Multiple completions d. High satisficing 2. Selection Bias a. Poor coverage b. Attitudinal and behavioral differences Concerns 1. Be sure that it is safe to ignore the offline population 2. Require that the research agency directly addresses the potential for bias and propose specific plans for correcting it 3. Understand that there are mode effects 4. Insist that online results be interpreted in the broader context of other sources of industry, business, and marketing information 5. Work with research agencies that understand the relevant industry and business issue as well as online methodologies Chapter 15 Coding: Assigning a code, usually a number to each possible response to each question • If it contains only structured questions or very few unstructured questions, it is precoded • Fixed field codes: A code in which the number of records for each respondent are the same and the same data appear in the same columns for all respondents Data cleaning: Consistency checks and treatment of missing responses • Consistency checks: Identify data that are out of range, that are logically inconsistent, or that have extreme values. Data with values not defined by the coding scheme are inadmissible. • Treatment of Missing Resp onses o Missing Responses: Represent values of a variable that are unknown, either because respondents provided ambiguous answers or their answers were not properly recorded (item nonresponse) – more than 10 % is an issue ▯ Substitute a neutral value – typically the mean response is substituted ▯ Casewise deletion: Cases or respondents with any missing responses are discarded from the analysis – could bias ▯ Pairwise deletion: Instead of discarding all cases with any missing values, the researcher uses only the cases or respondents with complete responses for each calculation • Sample size large • Few missing responses • Variables are not highly related Recoding variables (SPSS): Recode into different variables Variable respecification (Creating new variables in SPSS) Chapter 16 Frequency distribution: A mathematical distribution with the objective of obtaining a count of the number of responses associated with different values of one variable and to express these counts in percentage terms Measures of variability : Statistics that indicate the distribution’s dispersion • Range: The difference between the smallest and largest values of a distribution • Deviation from the mean: The difference between the mean and the observed value • Variance: The mean squared deviation of al l the values from the mean • Standard deviation: The square root of the variance Cross-tabulation: Describes two or more variables simultaneously and results in tables that reflect the joint distribution of two or more variables that have a limited number o f categories or distinct values Compute percentages in the direction of the independent variable Chi-square statistic: Test the statistical significance of the observed association in a cross -tabulation. Assists in determining whether a systematic association exists between the two variables Chapter 17 One sample t-test: Testing whether the population mean conforms to a given hypothesis Independent samples t-test: Two samples that are not experimentally related. The measurement of one sample has no effect on the values of the other sample Samples are independent if they are drawn randomly from different populations. For the purpose of analysis, data pertaining to different groups of respondents, males and females, and generally treated as independent samples Paired samples t test: A test for differences in the means of paired samples Analysis of variance (ANOVA): A test of means for more than two populations. The null hypothesis, typically, is that all means are equal. Must have a dependent variable that is metric (measured using an interval or ratio scale), and factors - one or more independent variables that are categorical (non - metric). Chapter 18 Product moment correlation : A statistic summarizing t he strength and direction of linear association between two metric variables AKA Pearson correlation coefficient, simple correla tion, Bivariate correlation, correlation coefficient Regression analysis: A powerful and flexible procedure for analyzing associative relationships between a metric- (interval) dependent variable and one or more metric - (interval or binary) independent variables (predictors) Dependent or criterion variables and independent or predictor variables in regression analysis arise from the mathematical relationship between the variables. Association not causality. Coefficient of determination : The proportion of variance in one variable associated with the variability in a second variable. Regression coefficient : When the regressio n line is linear (y = ax + b) the regression coefficient is the constant (a) that represents the rate of change of one variable (y) as a function of changes in the other (x); it is the slope of the regression line Multiple regression : A statistical technique that simultaneously develops a mathematical relationship between two or more independent variables and an interval -scaled dependent variable Multicollinearity: Two or more of the predictors (independent variables) in a regression model are moderately or highly correlated. Brand Positioning Research Perceptual mapping: How a customer thinks about products in a product category (2 -4 dimensions) Perceptions of customers are what count Perceptions differ by segment Key Questions: • What are the dimensions used? • Where are various brands on the map? • Where are segments of customers on the map? • How should we try to position our product? Multidimensional scaling: A class of procedures for representing perceptions and preferences of respondents spatially by means of a visual display Perceived for psychological relationships among stimuli are represented as geometric relationships among points in multidimensional space New Product Research Test markets: Testing a new product performance in a limited area of a national or regional target market Provides estimate of product performance in the respective country or region Expensive Time consuming Open to competitive sabotage • Standard test markets o Small representative markets where the firm conducts a full marketing campaign o Uses store audits, consumer and distributor surveys, and other measures to gauge product performance o Results are used to ▯ Forecast national sales and profits ▯ Discover product problems ▯ Fine-tune the marketing program o Challenges of standard test markets ▯ Cost ▯ Time ▯ Competitors can monitor the test as well ▯ Competitor interference ▯ Competitors gain access to the new product before introduction • Controlled test markets o Panels of stores that have agreed to car ry new products for a fee o Less expensive than standard test markets o Faster than standard test markets o Competitors gain access to the new product • Simulated test markets o The firm creates a shopping environment and notes how many consumers buy the new product and competing products o Provides measure of trial and the effectiveness of promotion o Researchers can interview consumers o Advantages of simulated test markets ▯ Less expensive than other test methods ▯ Faster ▯ Restricts access by competitors o Disadvantages of simulated test markets ▯ Not considered as reliable and accurate due to the controlled setting Conjoint analysis: Attempts to determine the relative importance consumers attach to salient attributes and the utilities they attach to the levels of attributes • Respondents are presented with stimuli that consist of combinations of attribute levels and asked to evaluate these stimuli in terms of their desirability • Conjoint procedures attempt to assign values to the levels of each attribute, so that the resulting values or utilities attached to the stimuli match, as closely as possible, the input evaluations provided by the respondents Segmentation Research Segmentation bases: Monday’s Lecture (12/7) Cluster analysis: Monday’s Lecture (12/7)
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