Hypothesis Flashcards

1
Q

H1 (first/alt. Hyp) EXAMPLE

A

There would be correlation between DV and IV

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2
Q

H0 EXAMPLE (NULL)

A

No correlation between DV and IV

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3
Q

What might affect findings?

A

Measures / definitions / samples

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4
Q

What if something is a chance finding?

A

We repeat

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5
Q

What is the P value and statistical significance

A

Gives probability of getting data if null = 0

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6
Q

Accepting H1 what does it mean?

A

means that the results of the study support the alternative hypothesis. In other words, there is evidence to suggest that the relationship or effect proposed in H1 is statistically significant. This indicates that the researcher’s initial hypothesis was correct or supported by the data collected in the study.

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7
Q

Rejecting H1

A

means that the results of the study do not support the alternative hypothesis
not enough evidence to suggest that the relationship or effect proposed in H1 is statistically significant. This indicates that the researcher’s initial hypothesis was not supported by the data collected in the study.

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8
Q

H0

A

Symbol for null hypothesis

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9
Q

U1 and u2

A

Population and other pop.

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10
Q

A hypothesis is a xxxxx xxxxxx about a phenomenon

A

Proposed explanation

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11
Q

Hypothesis definition

A

Precise statement of assumed relationship between variables.

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12
Q

Difference between null and alt.

A

The null hypothesis is the statement or claim being made (which we are trying to disprove) and the alternative hypothesis is the hypothesis that we are trying to prove and which is accepted if we have sufficient evidence to reject the null hypothesis.

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13
Q

How to decide if there is efficient evidence against null?

A
  • decide upon asignificance level. The5%significance level is a common choice for statistical test.
  • collect data and calculate thetest statisticand associatedp-valueusing the data.
    Assuming that the null hypothesis is true, thep-valueis the probability of obtaining a sample statistic equal to or more extreme than the observed test statistic.
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14
Q

parametric hypothesis

A

assumes that the data follows aNormal probability distribution(with equal variances if we are working with more than one set of data) . Aparametric hypothesis testis a statement about the parameters of this distribution (typically the mean). This can be seen in more detail in theParametric Hypotheses Tests section.

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15
Q

non-parametric

A

non-parametric testassumes thatthe data does not follow any distributionand usually bases its calculations on themedian. Note that although we assume the data does not follow a particular distribution it may do anyway

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16
Q

One-tailed tests

A

used when the alternative hypothesis states that the parameter of interest is either bigger or smaller than the value stated in the null hypothesis.

17
Q

Two-tailed tests

A

used when the hypothesis states that the parameter of interestdiffersfrom the null hypothesis but does not specify

18
Q

Type 1 error

A

made if we reject the null hypothesis when it is true (so should have been accepted).

19
Q

Type 2 error

A

Error made when we accept the null hyp when it is false - we should have rejected the null and accepted alt.