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Stats I Maastricht University > Task 2 > Flashcards

Task 2 Flashcards

1
Q

Statistics are also known as…

A

estimates

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2
Q

What do density curves represent?

A

the probability of a continuous random variable

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3
Q

Density curves are used on

A

histograms

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4
Q

What is the area under a density curve?

A

1

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5
Q

What kind of density curves are there?

A

normal, symmetric, skewed etc

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6
Q

Where is the mode on a density curve?

A

the highest point

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7
Q

How do you calculate the median on a density curve?

A

total area halved on each side

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8
Q

How do you locate quartiles on a density curve?

A

divide the area into quartiles

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9
Q

The larger the standard deviation, the larger the…

A

spread

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10
Q

Percentages for normal distribution

A

68% 95% 99.7%

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11
Q

Define standardizing

A

a linear transformation that transforms data into the standard scale of z-scores

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12
Q

What does a z score tell us?

A

tells us how many standard deviations the original observations fall away from the mean and in which direction

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13
Q

If observations are larger than the mean they are
a) positive
b) negative
when standardized

A

positive

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14
Q

Does standardizing affect the distributional characteristics e.g. shape and cumulative density?

A

no

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15
Q

What is the mean of the standard normal distribution?

A

0

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16
Q

What is the standard deviation of the standard normal distribution?

A

1

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17
Q

Define cumulative proportion

A

the proportion of observations a distribution that lie at or below a given value

18
Q

Does standardizing changes the slope and intercept of the line in our plot?

A

yes but the line does not turn

19
Q

How do we find the sampling distribution of the mean of x?

A

we take as many simple random samples of size 80 and calculate the mean for each sample

20
Q

What does the precision of an estimate depend on?

A

the spread of the sampling distribution

21
Q

What is the Central Limit Theorem?

A

draw a SRS of size n from any population with population mean and finite standard deviation

when n is large, the sampling distribution of the sample mean is approx normal

22
Q

Define exponential distribution

A

a process in which events occur continuously and independently at a constant average rate

23
Q

What does the mean and standard deviation equal in an exponential distribution?

A

1

24
Q

What is the formula to calculate the height under a density curve at a given point x?

A

see notes page 2

25
Q

Define unbiased estimate

A

applies to sample mean, expected value of sampling distribution of the statistic of interest = parameter of interest in the population

i.e. μx̅ = μ

26
Q

Define efficiency

A

an estimator is more “efficient” than another if the spread is smaller

27
Q

Efficiency is in relation to a ____ and variability is in relation to a ____

A

statistic, variable

28
Q

Define standard error

A

a measure of the statistical accuracy of an estimate, equal to the standard deviation of the theoretical distribution of a large population of such estimates (related to sampling distribution)

29
Q

Define central limit theorm

A

in some situations, when independent random variables are added, their properly normalized sum tends toward a normal distribution even if the original variables themselves are not normally distributed.

30
Q

What kind of variables are estimates?

A

random variables

31
Q

A sample is an example of a ___ ____

A

elementary outcome

32
Q

What kind of distribution is a sampling distribution?

A

a theoretical distribution

33
Q

What makes an estimate unbiased?

A

if averaged across an infinite number of estimations it would yield the parameter again

34
Q

Why is the standard deviation of a sampling distribution also known as the standard errror?

A

Because its the average deviations a mean will deviate from the actual mean when various samples are drawn

35
Q

How can we minimise the standard error?

A

drawing a larger sample e.g. larger than 25

36
Q

How can we make x bar a more efficient estimator?

A

increase sample size as it reduces standard error therefore predicts the population much better

37
Q

What do disjoint events look like on a contingency table?

A

=0

38
Q

Are distribution and bias related?

A

no

39
Q

What do outliers do to the mean?

A

skew it

40
Q

Always draw with replacement unless ….

A

conditional

41
Q

What distribution represents population distribution better?

a) sampling
b) sample scores

A

b

Stats I Maastricht University (5 decks)

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