Exam Review Units 1-6 Flashcards

(41 cards)

1
Q

What’re individuals?

A

individuals are objects described by a set of data

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2
Q

What’re variables?

A

variables are any characteristic of an individual

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3
Q

What’re categorical variables?

A

categorical variables are qualitative

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4
Q

What’er quantitative variables?

A

quantitative variables are numerical

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5
Q

What’s an outlier?

A

An outlier is an individual observation that falls outside the overall pattern of the data.

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6
Q

What’s nonresistance?

A

nonresistance is when extreme observations impact the value.

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7
Q

Examples of nonresistance?

A

mean and standard deviation

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8
Q

How can you display distributions with graphs?

A

displaying distributions with graphs:

  1. dotplots
  2. histograms
  3. stemplots
  4. time plots
  5. bar graphs
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9
Q

How to describe distributions with numbers? (important)

A

describing distributions with numbers:

  1. measures of center: mean, median, and mode
  2. measures of spread: range, interquartile range, standard deviation
  3. measuring position: quartiles, percentiles
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10
Q

What’s percentile?

A

percentile is the percent of the distribution that is at or to the left of the observation.

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11
Q

What does the normal distribution look like? (4) (important)

A

normal distribution:

  1. symmetric
  2. one peak
  3. bell shaped
  4. described by its mean and standard deviation.
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12
Q

What does the 68-95-99.7 rule apply to?

A

68-95-99.7 rule applies to NORMAL DISTRIBUTIONS.

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13
Q

What’s the 68-95-99.7 rule?

A

68-95-99.7 rule:

  1. 68% of the observations fall within 1 standard deviation of the mean
  2. 95% of the observations fall within 2 standard deviations of the mean
  3. 99.7% of the observations fall within 3 standard deviations of the mean
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14
Q

How to determine if data is normal?

A
  1. for histograms, stemplots, and box plots: look for a bell shape
  2. for normal probability plots: look for a straight line.
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15
Q

What’s a parameter?

A

a parameter is a number that describes the population.

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16
Q

Do we know the parameters?

A

NO! WE do not

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17
Q

what’s a statistic?

A

a statistic is a number that we can find using the sample data without using unknown parameters.

18
Q

What do we use a statistic for?

A

we use a statistic to estimate the unknown parameter

19
Q

what’s the sampling distribution?

A

the sampling distribution is the distribution of values taken by a statistic in all possible samples of the samite size from a population.

20
Q

When is a statistic unbiased?

A

a statistic is unbiased if the mean of its sampling distribution is equal to the true value of the parameter you’re estimating.

21
Q

What’s the variability of a statistic?

A

the variability of a statistic is the SPREAD of its SAMPLING DISTRIBUTION.

22
Q

What determines the spread of a sampling distribution?

A

These determine the spread of a sampling distribution:

  1. sampling design
  2. size of the sample
23
Q

How does sample size affect the spread?

A

as the sample size increases, the spread decreases and becomes smaller.

24
Q

When does the margin of error of a confidence interval get smaller? (3)

A

the margin of error of a confidence interval gets smaller when:

  1. the confidence “C” level decreases
  2. the population standard deviation decreases
  3. the sample size “n” increases.
25
Why do you do a test of hypothesis?
you do a test of hypothesis to assess the evidence provided by data against a null hypothesis H0 in favor of an alternative hypothesis Ha.
26
For hypothesis tests of significance, what's H0?
H0 is the null hypothesis
27
For hypothesis tests of significance, what's Ha?
Ha is the alternative hypothesis
28
What's a test of significance based on?
a test of significance is based on a TEST STATISTIC.
29
What's the p-value?
the p-value is the probability that the test statistic will take a value at least as extreme as the observed value if the NULL H0 is TRUE.
30
What do small p-values tell you?
small p-values tell you indicate strong evidence against the null hypothesis H0.
31
What happens if the p-value is equal to or less than the alpha "a"?
if the p-value is equal to or less than the alpha "a," the data are STATISTICALLY SIGNIFICANT at the alpha "a" significance level
32
When's the data STATISTICALLY SIGNIFICANT at the alpha "a" significance level?
the data is STATISTICALLY SIGNIFICANT at the alpha "a" significance level when the p-value is less than or equal to alpha "a."
33
What's a type 1 error? (important)
a type 1 error is when we reject the null hypothesis H0 when it is TRUE.
34
What's a type 2 error? (important)
a type 2 error is when we accept the null hypothesis H0 when in fact the alternative hypothesis Ha is true.
35
What's the power of a significance test?
The power of a significance test measures its ability to detect an alternative hypothesis
36
What's the power against a specific alternative?
the power against a specific alternative is the probability that the test will reject the null H0 when the alternative is true.
37
In a fixed level alpha "a" test, what's the level alpha "a"?
In a fixed level alpha "a" test, the level alpha "a" is the probability of a TYPE ONE (1) error
38
In a fixed level alpha "a" test, what's the power against a specific alternative?
In a fixed level alpha "a" test, the power against a specific alternative is 1 - beta "b" - beta is the probability of a Type TWO (2) error
39
In a fixed level alpha "a" test, what's the level beta "b"?
In a fixed level beta "b" test, the level beta "b" is the probability of a TYPE TWO (2) error
40
What's the standard error of a statistic?
The standard error of a statistic is the standard deviation of a statistic you estimate from the data.
41
When do you use a T Distribution?
you use a T distribution when you don't know the population's standard deviation σ.