MR test 1

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  1. Market Research
    Systematic search to produce information about market characterisitcs
  2. Marketing Research
    systematic research condcted to aid marketings decisions
  3. statistics
    the art and science of gathering, organzing, analyzing, interpretying and presenting numberical data for the purpose of making a more effective decision
  4. information
    processed data
  5. descriptive statistics
    gathers, organizes, analyzes and presents numerical data
  6. inferential statistics
    attempts to understand population characterisitcs based on data from a sample
  7. census
    a count of the entire population
  8. sample
    a portion of or extract from the population
  9. sample unit
    individual members of the sample
  10. variable
    a measurable factor that changes
  11. constant
    a measurable factor that does not change
  12. varaiblitiy
    the amount of dissimilarity
  13. qualititative variable
    the property being studied is nonnumeric in nature
  14. quantitative variable
    the property being studied can be reported numerically
  15. demographics
    variables used to describe or define the population being studied
  16. Secondary data
    information that has been collected for some other purpose
  17. primary data
    information gathered specifically for the research objectives at hand
  18. Open-ended
    presents no response options to the respondednt, expected to use his/her own words
  19. Open-ended unprobed
    • - "What were your impressions of the website?"
    • - freedom to respond with own words
    • - difficult to code and analyze
    • - may give one word answers
  20. open-ended probed
    • "can you think of anything more?"
    • -"did you have any other thoughts/impressions about the website?"
    • - more complete answers
    • - difficult to code and analyze
  21. closed-ended
    provides respone options that can be answered quickly and easily
  22. dichotomous closed-ended
    • "on your last visit, did you like or dislike the food at the red lobster?"
    • -simple to code and analyze
    • - oversimplifies response options?
  23. miltiple catergory closed-ended
    • "if you were to buy a DVD player tomorrow which brand would you most likely buy?
    • (a) panasonic (b) sony etc
    • - broad range
    • - simple to anaylaze/administer
    • - allow only one choice
    • -may alert respdodnes to options the were unware of
  24. scaled response
    uses a scale to measure a construct
  25. unlabeled scaled-response question
    • "on a scale of 1 to 7 how would you rate the red lobster on quality of food"
    • -
  26. labeled scaled response question
    "do you disagree strongly, disagree, agree, or agree strongly with the statement, "red lobster serves high quality food?"
  27. objective properties
    concrete, tangible, verifiable (age, income, etc)
  28. subjective properties
    cannot be directly observed because they are mental contrsucts(attitude, intentions, opinions, etc)
  29. scale develompent
    designin questions to measure the subkjective properties of an object
  30. categorical level of measurement
    scales of measure, qualitiative variables ( eg m/f, yes/no). disctinct categorys
  31. metric level of measurement
    scales: used for measuring quantitative variables (age, income, how many children, etc)
  32. Nominal scales (categorical, qualitative)
    • -use only labels (type of dwelling, occipation, gender, yes/no)
    • -least sophistacated (cannot perform advanced or sophistiacted stats with this data)
    • -"check the brand you would most leikley consider purchasing:"
    • -"do you recall seeing a delta airlines ad for carefree vacations in the past week?"
  33. ordinal scales (categorical, qualitative)
    • -"please rank each brand in terms of your preference (1 first choice, 2 2nd choice)
    • -in your opinion would you say the prices at walmart are": higher than sears, about the same as sears, lower than sears"
    • -rank order (indicate yoru first, second and third choice of brands)
    • -realtive size differences among objects.(cant tell how far apart the descriptors are on the scale- dont posses distance or origin)
  34. interval scales (metric)
    • "indicate your degree of agreement with the following statement by circling the appropriate number: "
    • "please rate pontiac firbired by checking the line that best corresponds to your evaluation of each item listed"
    • -distance is known or assumed to be equal (3 to 4 is same as 4 to 5)
    • -labels are on a continuum, equal distances apart for check lines
    • -higher level of measurement
  35. ratio scales (metric, quantitative)
    • "Please indicate your age" __years
    • "What is the probablity that you will use a lawyers services when you make a will? ___percent
    • -true zero origin exists ($ spent, time taken, years of college education)
    • -allows us to construct "ratios" when comparing results: "twice as heavy", three times as costly
    • -most sophistacted
  36. level of sophistication
    nominal (lowest), ordinal, interval, ratio (highest)
  37. modifited likert scale
    asked to indicate their degree of agreement or disagreement on a symmetri agree-disagree scale for a series of statements
  38. halo effect
    this is a general feeling toward an object that can bias responses to specific questions
  39. summated scale
    respondents reply with checkmarks from a list of options (check all that apply) the researcher can sum the checks to get a measure of the construct
  40. anchored scale
    one in which the endpoints are indentified with the beginning and ending number of the scale (eg 1=very dissasitified, 5=very satisfied)
  41. realiable
    one in which the same respondednt respond in the same way to an identical or nearly idenctical quesiotn
  42. valid
    the accuracy of the measurement a valid measure is on that is truthful
  43. data reduction
    • summarize (imporatant characteristics)
    • -get flavor of data, generalize sample,
  44. inferential analysis
    generalize results of sample to target population that it represents
  45. decriptive analyis
    • •Mean,
    • median, mode, standard deviation (“SD”), range

    • •Used
    • to describe the sample data matrix in such a way as to portray the
    • “typical” respondent and to reveal the general pattern of
    • responses.

    • •Typically
    • used early in the analysis; become foundations for subsequent analysis.
  46. Inferential
    • •“Inferential analysis” – generalize the results of the
    • sample to the target population that it represents.

    • •Meaning,
    • the researcher makes conclusions about the population based on the sample
    • results.

    • •Include
    • hypothesis testing; estimating true population values based on sample
    • information.
  47. Difference
    • •Used to test the difference between or among groups –
    • are the groups really different on this variable?

    • •For example: One group exposed to ad for Brand A; one
    • group has not seen the ad. Variable of
    • importance: purchase of brand. Are
    • there real and significant differences between the two groups?

    • •t-test for significant differences; analysis of variance
    • (ANOVA)
  48. .
    Associative Analysis
    • •Used to determine systematic relationships among
    • variables. “Associative analysis” investigates if and how two variables are related.

    • •Analysis may indicate how strong the association and /or
    • the direction (positive? negative?)

    • •Techniques include cross-tabulations (“cross-tabs”) and
    • correlations.
  49. 5.
    Predictive Analysis
    • •Used
    • to help the marketing researcher make predictions or forecasts about future
    • events.

    • •Regression
    • analysis, time series analysis are examples of techniques.
  50. Central tendency
    • -what response is most typical? Which is the most
    • frequent response?
    • - •Goal: to report a single piece of
    • information that describes the most typical response to a given question.
  51. Mode
    •“The value in a string of numbers that occurs MOST often.”
  52. Median
    • •Expresses the value that lies in the middle of an ORDERED set of values. It is
    • the value such that half the other
    • values are greater than the median, and half are less than it.
  53. Mean
    • The
    • average value characterizing
    • a set of numbers.
  54. Independent
    • a factor that causes or brings about a change
    • (e.g.,
    • money spent on advertising)
  55. Dependent
    • a factor that is changed (by the independent variable) (e.g., sales)
  56. Measures of
    • •Frequency
    • distribution/ Percentage Distribution
    • •Cumulative
    • Percentage Distribution
    • •Standard
    • Deviation, Range
  57. Frequency Distribution
    •A tabulation of the number of times that each value appears in a particular set of values.
  58. Measures of Variability – Range
    distance between the minimum and the maximum value in an ordered set of values.
  59. Measures of Variability – Standard Deviation (“SD”)
    • -indicates the degree of variation in the values translated into a normal distribution.
    • -
  60. ± 1.96 SD =?
    •indicates the limits within which 95% of the area under the curve lies
  61. ± 2.58 SD
    •indicates the limits within which 99% of the area under the curve lies
  62. Nominal
    1 Central Tendancy:
    2 Variability:

    • 1 Mode
    • 2 Frequency or percentage distribution
  63. Ordinal
    1 Central Tendancy:
    2 Variability:
    • 1. Median
    • 2. Cumulative percentage distribution
  64. Intervel or Ratio
    1 Central tendancy:
    2 Variability:
    • 1 Mean
    • 2 SD Range
  65. sample statistics
    Values that are computed from a sample.
  66. “Parameters”
    values that are computed from a complete census of the population
  67. µ
    population average
  68. x bar
    sample average
  69. σ
    Population SD
  70. S
    Sample SD
  71. π
    Population %
  72. p
    Sample %
  73. β
    Population slope
  74. b
    Sample slope
  75. Statistical inference
    • •a set of procedures in which the sample size and sample
    • statistics are used to make estimates of population parameters.
  76. n
    sample size
  77. Parameter Estimation
    of using sample information to compute an interval that describes the range of a parameter such as the population mean (µ) or the population percentage (π).
  78. Sample Statistic
    The mean or percentage is derived from a sample, so it is the sample statistic.
  79. •Standard Error (“SE”)
    measure of the variability in the sampling distribution
  80. Standard Error of the Mean
    Image Upload 1
  81. Standard Error of the Percentage
    • Image Upload 2
    • P + Q = 100
  82. The SE will be smaller for large sample sizes and larger with small sample sizes.
  83. When is p x q maximum?
  84. CI (95%) fo Std. error of mean =
    • =Mean ±1.96 (SE)
    • Image Upload 3
  85. CI (95%) for Std. Errof of % =
    • =p ± 1.96 (SE)
    • Image Upload 4
  86. Best estiamte tyhat the mena amount spent by US teens is 150/ week. 95% confident that population mean lies between 145.8 and 150
  87. Best estimate that 67% of milwaukee residence have been to a brewers game at least once in past 12 weeks. 99% confident that the populatin percentage lies between 60% and 70%
Card Set
MR test 1
marketing research test 1
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