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**Aaker, Kumar, Day Seventh Edition Instructor’s Presentation Slides**

Marketing Research Aaker, Kumar, Day Seventh Edition Instructor’s Presentation Slides

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**Hypothesis Testing: Basic Concepts and Tests of Association**

Chapter Seventeen Hypothesis Testing: Basic Concepts and Tests of Association

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**Hypothesis Testing : Basic Concepts and Tests of Associations**

Assumption (hypothesis) made about a population parameter Purpose of Hypothesis Testing To make a judgement about the difference between two sample statistics or the sample statistic and a hypothesized population parameter Marketing Research 7th Edition Aaker, Kumar, Day

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**The Logic of Hypothesis Testing**

Evidence has to be evaluated statistically before arriving at a conclusion regarding the hypothesis Depends on whether information generated from the sample is with fewer or larger observations Marketing Research 7th Edition Aaker, Kumar, Day

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**Hypothesis Testing Process**

Problem Definition Hypothesis Testing Process Clearly state the null and alternate hypotheses Choose the relevant test and the appropriate probability distribution Determine the degrees of freedom Determine the significance level Choose the critical value Compare test statistic and critical value Decide if one or two-tailed test Compute relevant test statistic Does the test statistic fall in the critical region? No Do not reject null Reject null Yes Marketing Research 7th Edition Aaker, Kumar, Day

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**Basic Concepts of Hypothesis Testing**

The null hypothesis (ho) is tested against the alternate hypothesis (ha) The null and alternate hypotheses are stated Decide upon the criteria to be used in making the decision whether to “reject” or "not reject" the null hypothesis Marketing Research 7th Edition Aaker, Kumar, Day

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**Basic Concepts of Hypothesis Testing (Contd.)**

The Three Criteria Used Are Significance Level Degrees of Freedom One or Two Tailed Test Marketing Research 7th Edition Aaker, Kumar, Day

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Significance Level Indicates the percentage of sample means that is outside the cut-off limits (critical value) The higher the significance level used for testing a hypothesis, the higher the probability of rejecting a null hypothesis when it is true (type I error) Accepting a null hypothesis when it is false is called a type II error and its probability is () Marketing Research 7th Edition Aaker, Kumar, Day

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**Significance Level (Contd.)**

When choosing a level of significance, there is an inherent tradeoff between these two types of errors Power of hypothesis test (1 - ) A good test of hypothesis ought to reject a null hypothesis when it is false 1 - should be as high a value as possible Marketing Research 7th Edition Aaker, Kumar, Day

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Degree of Freedom The number or bits of "free" or unconstrained data used in calculating a sample statistic or test statistic A sample mean (X) has `n' degree of freedom A sample variance (s2) has (n-1) degrees of freedom Marketing Research 7th Edition Aaker, Kumar, Day

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**One or Two-tail Test One-tailed Hypothesis Test**

Determines whether a particular population parameter is larger or smaller than some predefined value Uses one critical value of test statistic Two-tailed Hypothesis Test Determines the likelihood that a population parameter is within certain upper and lower bounds May use one or two critical values Marketing Research 7th Edition Aaker, Kumar, Day

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**Basic Concepts of Hypothesis Testing (Contd.)**

Select the appropriate probability distribution based on two criteria Size of the sample Whether the population standard deviation is known or not Marketing Research 7th Edition Aaker, Kumar, Day

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**Cross-tabulation and Chi Square**

In Marketing Applications, Chi-square Statistic Is Used As Test of Independence Are there associations between two or more variables in a study? Test of Goodness of Fit Is there a significant difference between an observed frequency distribution and a theoretical frequency distribution? Marketing Research 7th Edition Aaker, Kumar, Day

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**Cross-tabulation and Chi Square (Cont.)**

Statistical Independence Two variables are statistically independent if a knowledge of one would offer no information as to the identity of the other Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square As a Test of Independence**

Null Hypothesis Ho Two (nominally scaled) variables are statistically independent Alternative Hypothesis Ha The two variables are not independent Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square As a Test of Independence (Contd.)**

Chi-square Distribution A probability distribution Total area under the curve is 1.0 A different chi-square distribution is associated with different degrees of freedom Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square As a Test of Independence (Contd.)**

Degree of Freedom v = (r - 1) * (c - 1) R = number of rows in contingency table C = number of columns Mean of chi-squared distribution = Degree of freedom (v) Variance = 2v Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square Statistics (2)**

Measures of the difference between the actual numbers observed in cell i -- oi, and number expected (Ei) under independence if the null hypothesis were true 2 = (Oi - Ei)2 i= Ei With (r-1) (c-1) degrees of freedom R = number of rows C = number of columns Expected frequency in each cell Ei = pL * pA * n Where pL and pA are proportions for independent variables Marketing Research 7th Edition Aaker, Kumar, Day

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**Strength of Association**

Measured by contingency coefficient C = x o< c < 1 x2 + n 0 - no association (i.E. Variables are statistically independent) Maximum value depends on the size of table-compare only tables of same size Marketing Research 7th Edition Aaker, Kumar, Day

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**Limitations As an Association Measure**

It Is Basically Proportional to Sample Size Difficult to interpret in absolute sense and compare cross-tabs of unequal size It Has No Upper Bound Difficult to obtain a feel for its value Does not indicate how two variables are related Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square Goodness of Fit**

Used to investigate how well the observed pattern fits the expected pattern Researcher may determine whether population distribution corresponds to either a normal, poisson or binomial distribution Marketing Research 7th Edition Aaker, Kumar, Day

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**Chi-square Degrees of Freedom**

Employ (k-1) rule Subtract an additional degree of freedom for each population parameter that has to be estimated from the sample data Marketing Research 7th Edition Aaker, Kumar, Day

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