Marketing 4050 Exam 2

5 Types of statistical Analysis

1. Descriptive analysis 2. Inferential analysis 3. Differences analysis 4. Associative analysis 5. Predictive analysis

5 steps involved in computing confidence intervals for a mean or percentage

1. Determine the sample statistic 2. Identify the sample size, n 3. Determine the variability in the sample for that statistic 4. Decide on the desired level of confidence 5. Perform the computations to determine the upper and lower boundaries of the confidence interval range (typically at 95%)

4 types of measures of variability

1. Frequency (percentage) distribution -Nominal 2. Range - Ordinal 3. Standard deviation - Interval/ Ratio 4. variance

3 measures of central tendency

1. Mode- Nominal 2. Median- Ordinal 3. Mean- Interval/ratio

Types of relationships between two variables

1. Non-monotonic 2. Monotonic 3. Linear 4. Curvilinear

3 criteria for selecting test-market cities

1. Representativeness 2. Degree of isolation 3. Ability to control distribution and promotion

What are the 4 types of test markets?

1. Standard 2. Controlled 3. Electronic 4. Simulated

How can we assess the validity of an experiment?

1. the observed change in the dependent variable is, in fact, due to the independent variable 2. the results of the experiment apply to the "real world" outside the experimental setting.

Alternative hypothesis

A true difference between the compared means (or%)

Extraneous variables

Are all of the variables other than the independent variables that may have an effect on the dependent variables

Independent Variables

Are variables over which the researcher has control and wishes to manipulate to measure the effect on the dependent variable.

Dependent Variables

Are variables that are measured in response to changes in independent variables

E

Experimental effect- that is, the change in the dependent variable due to the independent variable

Interval Scale

Mean Standard deviation &/ or Range

Ration Scale

Mean Standard deviation &/ or Range

Curvilinear

Means some smooth curve pattern describes the association

Ordinal Scale

Median Cumulative percentage distribution/ Range

Nominal Scale

Mode Frequency (percentage) distribution

Null hypothesis

No difference between the means (or%) being compared

R

Random assignment of subjects to experimental and control groups

Variance

Standard deviation squared

X

The manipulation, or change, of an independent variable

O

The measurement of a dependent variable

Population parameters (Greek Letters)

Values that are computed from a complete census, which are considered to be precise and valid measures of the population

Sample statistics

Values that are computed from information provided by a sample

Hypothesis testing

a statistical procedure used to "accept" or "reject" the hypothesis based on sample information

Hypothesis

an expectation of what the population parameter value is

Confidence intervals

are the degree of accuracy desired by the researcher and stipulated as a level of confidence in the form of a range with a lower boundary and an upper boundary.

Laboratory experiments

are those in which one or more independent variables are manipulated and measures of the dependent variable are taken in an artificial setting for the purpose of controlling all extraneous variables that may affect the dependent variable

Field experiments

are those in which the independent variables are manipulated and the measurements of the dependent variables are taken in their natural setting

Range

identifies the maximum and minimum values in a set of numbers

Standard deviation

indicates the degree of variation in a way that can be translated into a bell-shaped curve distribution

Linear relationship

is a "straight-line association" between two scale variables. Means the two variables have a "straight-line" relationship

Experimental group

is a group that has been exposed to a change in the independent variable

Control group

is a group whose subjects have not been exposed to the change in the independent variable

Standard error

is a measure of the variability in a sampling distribution

Posttest

is a measurement of the dependent variable that is taken after changing the independent variable

Pretest

is a measurement of the dependent variable that is taken prior to changing the independent variable

Experimental Design

is a procedure for devising an experimental setting so that a change in a dependent variable may be attributed solely to the change in an independent variable.

Statistical inference

is a set of procedures in which the sample size and sample statistic are used to make an estimate of the corresponding population parameter

Experiment

is a type of study in which one or more independent variables are manipulated to see how one or more dependent variables are affected, while also controlling the effects of additional extraneous variables.

Test marketing

is conducting an experiment or study in a field setting to evaluate a new product or service or other elements of the marketing mix

Simulated test markets (STM)

is one in which a limited amount of data on consumer response to a new product is fed into a model containing certain assumptions regarding planned marketing programs, which generates likely product sales volume.

Electronic test market

is one in which a panel of consumers has agreed to carry identification cards that each consumer presents when buying goods and services

Standard test market

is one in which the firm tests the product or marketing-mix variables through the company's normal distribution channels

Controlled test market

is one that is conducted by outside research firms that guarantee distribution of the product through prespecified types and numbers of distributors.

A/B testing

is testing two alternatives (A and B) to see which one performs better.

Mean

is the arithmetic average of a set of numbers

Internal validity in an experimental study

is the extent to which the researcher is certain that a change in a dependent variable is actually due to the independent variable

Mode

is the number appearing most often in a set of numbers

Non-monotonic relationship

means two variables are associated but only in a very general sense

Monotonic relationship

means you know the general direction (increasing or decreasing) of the relationship between two variables

External validity

refers to the extent to which a researcher can be certain that a relationship observed between independent and dependent variables during an experiment would occur under real-world conditions

Measures of variability

reveal typical difference between the values in a set of values

Frequency (percentage) distribution

reveals the number (percent) of occurrences of each number in a set of numbers

Data analysis

the process of describing a dataset by computing a small number of statistics that characterize various aspects of the dataset

Median

the value whose occurrence lies in the middle of a set of ordered values

ANOVA concept

used when comparing the means of three or more groups