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PSU Sophomore > STAT 200 Final > Flashcards

STAT 200 Final Flashcards

(60 cards)

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1
Q

Population parameter

A

Fixed value that we usually don’t know

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2
Q

Sample statistic

A

Known value that we achieve by taking a random sample from population

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3
Q

Simple random sample

A

Sample from population is chosen randomly

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4
Q

A good experiment uses

A

simple random sample and random assignment

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5
Q

Random assignment

A

Assigning to groups (control or treatment) randomly

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6
Q

If no random assignment, then

A

NO causation

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7
Q

If sample was not randomly selected, then

A

NEVER generalize to population

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8
Q

Observational study

A

Survey

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9
Q

Randomized experiment

A

Change the variables

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10
Q

Matched pairs study

A

Match 2 samples in group or compare as group

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11
Q

More likely, tend to

A

association

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12
Q

Lead to, affect, cause

A

Causation

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13
Q

Proportion or risk

A

Topic on interest / Total # in category

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14
Q

Odds (ex. 45 to 20)

A

with outcome/ # without outcome

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15
Q

Relative risk (ex. you are 5.2 times more likely to get lung cancer if you smoke compared to a non-smoker)

A

risk1/risk2 (proportion 1/proportion 2)

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16
Q

5 # summary

A

Min, Q1, Median, Q3, Max

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17
Q

IQR

A

Q3-Q1

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18
Q

If median is closer to Q1

A

right-skewed

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19
Q

If median is closer to Q3,

A

left-skewed

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20
Q

Mean is greater than median

A

Right skewed

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21
Q

Mean is less than median

A

Left skewed

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22
Q

Large standard deviation

A

More variability and wide graph
Straight graph

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23
Q

Smaller std dev

A

Less variability and narrow graph

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24
Q

Correlation does NOT imply

A

causation

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25
Sampling distribution center
Population parameter
26
As sample size increases, SE
decreases
27
Confidence interval
CI statistic +- (multiplier)(SE)
28
Bootstrap center
Sample statistic (ORIGINAL)
29
Type I error
false positive
30
Type II error
false negative
31
Proportions use which distribution?
Z
32
Means use which distribution?
t
33
Central limit theorem for Z distribution (Proportion)
np and n(1-p) >10
34
Central limit theorem for t distribution (mean)
n>30 or looks symmetrical
35
Z multiplier is NOT the
Z statistic
36
Paired t test
Same group of individuals (2 means for each case)
37
Difference in means
Not same group (or 2 sample t-test)
38
Linear regression hypotheses
B1=0 B1 does not = 0
39
If b1 = 0,
no linear correlation
40
If b1 does not equal, >, < 0
Pos, neg, or any relationship at all
41
R2 tells us
how close data point is to line of best fit
42
R2 interpretation
Approximately % of the variability in ___ can be explained by the predictor _____
43
Chi-Square Test for association
Expected counts must be greater than or equal to 5
44
Randomization center
null value
45
Larger sample size,
Smaller SE, Narrower CI
46
Smaller sample size,
Larger SE, Wider CI
47
Random assignment CANNOT
generalize to the population
48
Explanatory variable on
x axis
49
Response variable on
y axis
50
A smaller standard deviation's graph will
look more symmetrical
51
1 man in 7 will be diagnosed with cancer 1 in 39 will die of prostate cancer
Individual risk
52
Residual is positive when
point is above slope
53
Residual is negative when
point is below slope
54
If the proportion of undergrad students who vape is 1/8, what are the odds that a student vapes?
1/7
55
Larger standard deviation,
larger range
56
z score
number of standard deviations from the mean
57
You cannot use linear regression when
the data is not linear
58
Use which distribution to construct a confidence interval?
bootstrap
59
Construct the 92% CI for the correlation. What percentiles will we use as cutoffs?
4th and 96th
60
Increasing the sample size, changes the p value and t value how?
p value decrease t value larger

PSU Sophomore (4 decks)

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