(R11) Hypothesis Testing Flashcards

1
Q

Null Hypothesis

A

The hypothesis that the researcher wants to reject, denoted Ho; The hypothesis that is actually tested and is the basis for the selection of the test statistics.

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2
Q

Alternative hypothesis

A

The hypothesis that we want to validate

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3
Q

Steps in hypothesis testing

A
  1. State the hypothesis
  2. Identify the appropriate test statistic (t or z) and its probability distribution
  3. Specify level of confidence
  4. State the decision rule
  5. Collect data and calculate the test statistic
  6. Make the decision
  7. Make the real world decision
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4
Q

Two-tailed test for the population mean

A

Ho: u = uo,
Ha: u =/ uo

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5
Q

One-tailed test for the population mean

A

Ho: u <= uo
Ha: u > uo

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6
Q

Test-Statistic Calculation

A

(Sample Statistic - Hypothesized Value) / SE of sample

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7
Q

2 Types of Errors in Hypothesis Testing

A

Type 1: The rejection of null hypothesis when it is actually true (alpha = probability of type 1 error)
Type 2: The failure to reject the null hypothesis when it is actually false

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8
Q

Power of a test in hypothesis testing

A

Probability of correctly rejecting the null (rejecting the null when it is false)

= 1 - probability of type two error

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9
Q

When doing hypothesis testing, what must be compared to the test statistic?

A

Compare to the critical value (use alpha to look up critical value in tables).

For one tailed tests, if the test statistic is greater than the critical value, you reject the null

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10
Q

P-Value

A

Smallest level of significance at which null hypothesis can be rejected; the smaller the p-value the stronger the evidence (if you have p-value of .0342, you can reject null hypothesis at an alpha of .05 but not .01)

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11
Q

For two tailed tests with an alpha of 10%, how much percentage would be in each tail?

A

Divide alpha by two since its a two tailed test (5% in each tail)

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12
Q

Hypothesis for testing the differences between means

A

Ho: u1 - u2 = 0
Ha: u1 - u2 =/ 0

You can also change the equal signs to greater than or less then

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13
Q

Pooled variances

A

Used with t-statistics for testing the means of two normally distributed populations are equal, when the variances of the population are unknown but assumed to be equal.

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14
Q

Chi-square Test

A

Test used for hypothesis testing concerning the variance of a normally distributed population.

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15
Q

Chi-Square Calculation

A

ChiSquare = (n-1)s^2 / sigma^2

s= sample variance
sigma^2 = hypothesized population variance
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16
Q

F-Test

A

Test concerned with the equality of the variances of two populations, used when the populations are normally distributed.

17
Q

F-Test Calculation

A

F = s1^2 / s2^2

s1^2 = Variance of s1
s2^2 = Variance of s2
18
Q

Parametric Tests

A

Tests that rely on assumptions regarding the distribution of the population and are specific to population parameters

19
Q

Nonparametric tests

A

Tests that do no consider a particular population parameter or have few assumptions about the population that is sampled.