Exam (elaborations)

inferential Statistics

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Inferential Statistics

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Inferential Statistics

Hypothesis testing - answer-A statement about the parameters; support or contradict; based on sample evidence (stat) and probability, used to test claims regarding a characteristic (parameter) Population - answer-All subjects or objects possessing some common specified characteristic. Arbitraril...

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inferential statistics

Institution Inferential Statistics
Course Inferential Statistics

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INFERENTIAL STATISTICS SAMPLE QUESTIONS AND ANSWERS

Inferential statistics - answer-Making inferences, hypothesis testing,
determining relationship

Point estimation - answer-Estimate a population parameter

Confidence interval - answer-Estimate a population parameter with
confidence

Hypothesis testing - answer-A statement about the parameters; support or
contradict; based on sample evidence (stat) and probability, used to test
claims regarding a characteristic (parameter)

Population - answer-All subjects or objects possessing some common
specified characteristic. Arbitrarily defined by naming its unique properties

Parameter - answer-A measurable characteristic do a population (u, sigma...)

Sample - answer-Smaller group of subjects or objects selected from a large
group (population)

Statistic - answer-A measurable characteristic of a sample (x,s,z,t...)

Null hypothesis - answer-There is no difference or association between
variables that is any greater than expected y chance

Alternative hypothesis - answer-The relationship or association or difference
that the researcher actually believes to be present; research hypothesis

Steps for hypothesis testing - answer-1. Establish hypothesese (null and alt)
2. Significance level- determine what alpha to use to determine statistical
significance
3. Stats test- determine what test to use
4. Compare the distribution of the stat to the distribution under the null and
report p- value
5. Decision rule: reject or fail to reject null

Significance level - answer-Alpha is the probability of making a type 1 error;
specified as a small probability range, usually 0.05.

P value interpretation - answer-- <1%= overwhelming evidence that
supports the alt. hyp.
-1-5%= strong evidence to support alt hyp.

[Type here]

, 1
1

-5-10%= weak evidence to support alt hyp
->10%= no evidence that supports the alt. hyp

Type 1 Error - answer-(alpha): reject null when null is true

Type II Error - answer-Beta: we don't reject the null when the null is false

Point estimate - answer-When a parameter is being estimated as a single
number

Interval estimate - answer-When a parameter is being estimated as a range
of scores

Confidence interval - answer-The level of certainty that the true score falls
within a specific range. The smaller the range the less the certainty.

95% CI formula - answer-u=X+-1.96(sigma/sqrt n)

99%CI Fromula - answer-u=X+-2.58(sigma/sqrt n)

Test statistic Z - answer-Z= xbar-u/sigma/sqrt n

T test - answer-A group of statistics used to determine if a significance
difference exists between the means of two sets of data; small n (<30)

Sampling distribution - answer-Describes probabilities associated with a
statistic when a random sample is drawn from a population

Why t test instead of Z test? - answer-Z requires knowledge of the population
standard deviation sigma~ usually don't have this information. Use t test for
this

T test formula - answer-t=Xbar-u/S/sqrt n
Where u is the population mean, Xbar is the sample mean and S is the
estimator for population standard deviation.

One sample t test - answer-Compares the mean score of a sample to a
known value~ usually the population mean

One sample t test data requirement - answer-Continuous data, small sample,
known population mean u

One sample t test assumptions - answer-Data is normally distributed,
individual observations are independent, sample is randomly drawn

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