Statistic Procedures (Except the proportion tests)

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63 Terms

1
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What is a One Sample T-Test

Used to test a claim about a population mean

2
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Null Hypothesis for One Sample T-Test

μ = #

3
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Alternate Hypothesis for One Sample T-Test

μ > #
μ < #
μ ≠ #

4
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Conditions for One Sample T-Test

1) Sample is random
2) Sampling distribution is approximately normal ( a. If n≥30 , assumed by CLT b. if n≤30 this condition needs to be checked with a histogram)

5
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What is in the Calculation step of a One Sample T-Test

T-value, P-Value and Degrees of Freedom

6
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Formula for One Sample T-Test

Calculator: Stats, Tests, 2

<p>Calculator: Stats, Tests, 2</p>
7
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Formula for Degrees of Freedom in a One Sample T-Test

df = n-1

8
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Conclusion for One Sample T-Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

9
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What is a One Sample T-Interval?

Used to give a plausible range of values for population mean

10
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Conditions for One Sample T-Interval

1) Sample is random
2) Sampling distribution is approximately normal ( a. If n≥30 , assumed by CLT b. if n≤30 this condition needs to be checked with a histogram)

11
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What is needed for the Calculation step of a One Sample T-Interval

Range of values, Degrees of Freedom

12
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Formula for One Sample T-Interval

Calculator: Stats, Tests, 8

<p>Calculator: Stats, Tests, 8</p>
13
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Formula for Degrees of Freedom in a One Sample T-Interval

df = n-1

14
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Conclusion for One Sample T-Interval

We are ___% confident that the true mean of ___ (context) lies between ___(lower bound) and ___(upper bound) ___ (units)

15
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What is a Two Sample T-Test

Used to test a claim about a difference of population means

16
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Null Hypothesis for Two Sample T-Test

H0: μ1 = μ2

17
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Alternate Hypothesis for Two Sample T-Test

μ1 > μ2
μ1 < μ2
μ1 ≠ μ2

18
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What is needed in the Calculation Step of a Two Sample T-Test

T-Value, P-Value and Degrees of Freedom

19
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Formula for Two Sample T-Test

Calculator: Stats, Tests, 4,

<p>Calculator: Stats, Tests, 4, </p>
20
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Conclusion for Two Sample T-Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

21
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What is a Two Sample T-Interval

Used to give a plausible range of values for a difference in population means

22
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Conditions for a Two-Sample T-Interval

1) Sample are random and independent
2) Sampling distributions are approximately normal ( a. If n1,n2≥30, assumed by CLT b. if n1,n2≤30 this condition needs to be checked with a histogram(s)

23
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What is needed in the Calculation step of a Two Sample T-Interval

T-Value, P-Value and Degrees of Freedom

24
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Formula for Two Sample T-Interval

Calculator: Stats, Tests, 0

<p>Calculator: Stats, Tests, 0</p>
25
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Conclusion for Two Sample T-Interval

We are ___% confident that the true difference in the mean of ___ (context) lies between ___(lower bound) and ___(upper bound) ___

26
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What is a Paired T-Test

Used to test a claim about a difference population means for dependent data

27
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Null Hypothesis for Paired T-Test

μd = 0

28
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Alternate Hypothesis for Paired T-Test

μd > 0
μd < 0
μd ≠ 0

29
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Conditions for Paired T-Test

1) Matched Pairs Design: Subjects are randomly assigned treatments
Repeated Measures Design: The order in which subjects received treatments was random
Sample is random (sample, not experiment)

2) Sampling Distribution of differences is approximately normal

30
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What do you need for the Calculation step of a Paired T-Test

T-Value, P-value, and Degrees of Freedom

31
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Formula for Paired T-Test

Calculator: Stats, Tests, 2

<p>Calculator: Stats, Tests, 2</p>
32
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Formula for Degrees of Freedom in a Paired T-Test

df = n-1

33
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Conclusion for Paired T-Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

34
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What is a Paired T-Interval

Used to give a plausible range of values for the difference in population means for dependent data

35
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Conditions for a Paired T-Interval

1) Matched Pairs Design: Subjects are randomly assigned treatments
Repeated Measures Design: The order in which subjects received treatments was random
Sample is random (sample, not experiment)

2) Sampling Distribution of differences is approximately normal

36
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What is needed for the Calculation step of a Paired T-Interval

Range of values and Degrees of Freedom

37
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Formula for Paired T-Interval

Calculator: Stats, Tests, 8

<p>Calculator: Stats, Tests, 8</p>
38
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Formula for Degrees of Freedom in a Paired T-Interval

df = n-1

39
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Conclusion for Paired T-Interval

We are ___% confident that the true differences in the mean of ___ (context) lies between ___(lower bound) and ___(upper bound) ___

40
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What is a X² Goodness of Fit Test

Used to test a claim that the proportions of a single categorical variable are consistent with some expectation

41
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Null Hypothesis for X² Goodness of Fit Test

The data is consistent with what we expect

42
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Alternate Hypothesis for X² Goodness of Fit Test

The data is no consistent with what we expect

43
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Conditions for X² Goodness of Fit Test

1) Sample is random
2) Expected frequencies are at least 5 (Create a table with Observed and Expected, computed using the given proportions/ratios for the sub-categories)

44
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What is needed for the Calculation step of a X² Goodness of Fit Test

X² Value, P-value, and Degrees of Freedom

45
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Formula for X² Goodness of Fit Test

Calculator: Stats, Tests, D

<p>Calculator: Stats, Tests, D</p>
46
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Formula for Degrees of Freedom in a X² Goodness of Fi

df = n-1

47
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Conclusion for X² Goodness of Fit Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

48
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What is a X² Independence Test

Used to test if two categorical variables are independent of one another

49
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Null Hypothesis for X² Independence Test

There is no association between ___ and ___

50
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Alternate Hypothesis for X² Independence Test

There is an association between ___ and ___

51
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Conditions for X² Independence Test

1) Sample is Random
2) Expected Frequencies are at least 5 | (row total*column total)/grand total

52
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What is needed for the Calculation step of the X² Independence Test

X² Value, P-Value, and Degrees of Freedom

53
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Formula for X² Independence Test

Calculator: Stats, Tests, C

<p>Calculator: Stats, Tests, C</p>
54
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Formula for Degrees of Freedom of a X² Independence Test

df = (r-1)(c-1)

55
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Conclusion for X² Independence Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

56
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What is a X² Homogeneity Test

Used to test if the distribution of the sub-categories of a single categorical variable is the same for multiple populations

57
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Null Hypothesis for X² Homogeneity Test

The distribution of ___ is the same for ___ and ___

58
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Alternate Hypothesis for X² Homogeneity Test

The distribution of ___ is not the same for ___ and ___

59
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Conditions for X² Homogeneity Test

1) Samples are random and independent
2) Expected frequencies are at least 5 (row total*column total)/grand total

60
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What do you need for the Calculation step of the X² Homogeneity Test

X² Value, P-value, Degrees of Freedom

61
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Formula for X² Homogeneity Test

Calculator: Stats, Tests, C

<p>Calculator: Stats, Tests, C</p>
62
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Formula for Degrees of Freedom for X² Homogeneity Test

df = (r-1)(c-1)

63
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Conclusion for X² Homogeneity Test

Since the P-value of ___ is less than/greater than the α-level of .05, we reject/fail to reject the H0. In other words, there is/isn’t statistically significant evidence to support the HA that ___ (context)

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