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MKTG 460 > Marketing Research Quiz #3 > Flashcards

Marketing Research Quiz #3 Flashcards

1
Q

Null Hypothesis

A

A statement suggesting no expected difference or effect. If the null hypothesis is not rejected, no changes will be made.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 312). Pearson Education. Kindle Edition.

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2
Q

Test Statistic

A

A measure of how close the sample has come to the null hypothesis. It often follows a well-known distribution, such as the normal, t, or chi-square distribution.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 313). Pearson Education. Kindle Edition.

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3
Q

Z-Test

A

A hypothesis test using the standard normal distribution.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 313). Pearson Education. Kindle Edition.

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4
Q

Type I Error

A

An error that occurs when the sample results lead to the rejection of a null hypothesis that is, in fact, true. Also known as alpha (a) error.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 313). Pearson Education. Kindle Edition.

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5
Q

Type II Error

A

An error that occurs when the sample results lead to nonrejection of a null hypothesis that is, in fact, false. Also known as beta (b) error.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 314). Pearson Education. Kindle Edition.

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6
Q

P Value

A

The probability of observing a value of the test statistic as extreme as, or more extreme than, the value actually observed, assuming that the null hypothesis is true.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 314). Pearson Education. Kindle Edition.

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7
Q

Cross-Tabulation

A

A statistical technique that 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 of categories or distinct values.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 317). Pearson Education. Kindle Edition.

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8
Q

Chi-square Statistic

A

The statistic used to test the statistical significance of the observed association in a cross-tabulation. It assists in determining whether a systematic association exists between the two variables.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 320). Pearson Education. Kindle Edition.

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9
Q

Chi-square Distribution

A

A skewed distribution whose shape depends solely on the number of degrees of freedom. As the number of degrees of freedom increases, the chi-square distribution becomes more symmetrical.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 320). Pearson Education. Kindle Edition.

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10
Q

Parametric Tests

A

Hypothesis-testing procedures that assume the variables of interest are measured on at least an interval scale.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 334). Pearson Education. Kindle Edition.

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11
Q

T Test

A

A hypothesis test using the t distribution, which is used when the mean is known, the standard deviation is unknown and is estimated from the sample.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 335). Pearson Education. Kindle Edition.

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12
Q

T Statistic

A

A statistic that assumes the variable has a symmetric, bellshaped distribution; the mean is known (or assumed to be known); and the population variance is estimated from the sample.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 335). Pearson Education. Kindle Edition.

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13
Q

Standard Error

A

The standard deviation of the mean or proportion.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 335). Pearson Education. Kindle Edition.

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14
Q

T Distribution

A

A symmetric bell-shaped distribution that is defined by n - 1 degrees of freedom.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 335). Pearson Education. Kindle Edition.

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15
Q

F Test

A

A statistical test of the equality of the variances of two populations.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 340). Pearson Education. Kindle Edition.

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16
Q

F statistic

A

A statistic that is calculated as the ratio of two sample variances by dividing the larger sample variance by the smaller sample variance.

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17
Q

F distribution

A

A frequency distribution that depends on two sets of degrees of freedom: the degrees of freedom in the numerator and the degrees of freedom in the denominator.

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18
Q

paired samples

A

In hypothesis testing, the observations are paired so that the two sets of observations relate to the same respondents.

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19
Q

Level of Significance

A

The probability of making a type I error, denoted by a.

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20
Q

power of a test

A

The probability of rejecting the null hypothesis when it is, in fact, false and should be rejected. It is (1 - b).

21
Q

Cross Tabulation Steps

A

When conducting cross-tabulation analysis in practice, it is useful to follow these steps (see Figure 11.10):

  1. Construct the cross-tabulation table.
  2. Test the null hypothesis to see that there is no association between the variables using the chi-square statistic (see the procedure described in Figure 11.5).
  3. If you fail to reject the null hypothesis, there is no relationship.
  4. If H0 is rejected, determine the strength of the association using an appropriate statistic (phi-coefficient, contingency coefficient, or Cramer’s V) as discussed earlier in this chapter.
  5. If H0 is rejected, interpret the pattern of the relationship by computing the percentages in the direction of the independent variable, across the dependent variable. Draw marketing conclusions.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 321). Pearson Education. Kindle Edition.

22
Q

Parametric Test

A

Hypothesis-testing procedures that assume the variables of interest are measured on at least an interval scale.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 334). Pearson Education. Kindle Edition.

23
Q

Regression Analysis

A

A statistical procedure for analyzing associative relationships between a metric dependent variable and one or more metric independent variables.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 348). Pearson Education. Kindle Edition.

24
Q

paired comparison scaling

A

A comparative scaling technique in which a respondent is presented with two objects at a time and asked to select one object in the pair according to some criterion. The data obtained are ordinal in nature.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 190). Pearson Education. Kindle Edition.

25
Q

paired comparison scaling

A

A comparative scaling technique in which a respondent is presented with two objects at a time and asked to select one object in the pair according to some criterion. The data obtained are ordinal in nature.

Malhotra, Naresh K.. Essentials of Marketing Research: A Hands-On Orientation (Page 190). Pearson Education. Kindle Edition.

26
Q

General Qualification of Field Workers

A

Healthy.
Outgoing.
Communicative. Pleasant appearance. Educated.
Experienced.

27
Q

Coding

A

assigning a code, usually a number, to each possible response to each question.

28
Q

Coding Questions

A

Fixed field codes, which mean that the number of records for each respondent is the same and the same data appear in the same column(s) for all respondents, are highly desirable.
If possible, standard codes should be used for missing data. Coding of structured questions is relatively simple, since the response options are predetermined.
In questions that permit a large number of responses, each possible response option should be assigned a separate column.

29
Q

codebook

A

contains coding instructions and the necessary information about variables in the data set.

30
Q

Fieldmap for data collection process

A

Chapter 10

31
Q

Frequency distribution

A

A frequency distribution indicates the shape of the distribution of the variable and the extent of missing, illegitimate and extreme responses.

32
Q

central tendency

A

the extent to which the values of a numerical variable group around a typical or central value.

33
Q

Variation

A

the amount of dispersion or scattering away from a central value that the values of a numerical variable show.

34
Q

Shape

A

the pattern of the distribution of values from the lowest value to the highest value.

35
Q

Median

A

Middle value in the ordered array

36
Q

Mode

A

Most frequently observed value

37
Q

Mode

A

Most frequently observed value

38
Q

How do you define whether a value is an outlier?

A

Can be statistically determined using a z score

39
Q

How do you define whether a value is an outlier?

A

Can be statistically determined using a z score

40
Q

Computing the Z-Score of a data value

A

Subtract the mean and divide by the standard deviation.

41
Q

Definition of an extreme outlier

A

Z-score is less than -3.0 or greater than +3.0.

42
Q

Skewness (SKEW)

A

Measures the extent to which data values are not symmetrical

43
Q

Kurtosis (KURT)

A

Kurtosis affects the peakedness of the curve of the distribution—that is, how sharply the curve rises approaching the center of the distribution

44
Q

null hypothesis

A

is a statement of the status quo, one of no difference or no effect. If the null hypothesis is not rejected, no changes will be made.

45
Q

alternative hypothesis

A

is one in which some difference or effect is expected. Accepting the alternative hypothesis will lead to changes in opinions or actions.

46
Q

Test statistic

A

measures how close the sample has come to the null hypothesis and follows a well-known distribution, such as the normal, t, or chi-square.

47
Q

Cross-tabulation

A

A cross-tabulation describes two or more variables simultaneously. Results in tables that reflect the joint distribution of two or more variables with a limited number of categories or distinct values,

48
Q

casewise deletion

A

A method for handling missing responses or values in which cases or respondents with any missing values are discarded from the analysis. pairwise deletion A method of handling missing responses or values in which all cases, or respondents, with any missing values are not automatically discarded; rather, for each calculation, only the cases or respondents with complete responses are considered.

49
Q

pairwise deletion

A

A method of handling missing responses or values in which all cases, or respondents, with any missing values are not automatically discarded; rather, for each calculation, only the cases or respondents with complete responses are considered.

MKTG 460 (1 decks)

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