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MHA622 - Biostatistics > Week 4 - Confidence Intervals > Flashcards

Week 4 - Confidence Intervals Flashcards

1
Q

Most common CIs?

A

90%, 95% or 99%

(0% to 100% are possible, though not usually desirable)

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2
Q

Hypothesis testing involves generating an ____________ about the ___________ ____________.

A

hypothesis, population parameter

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3
Q

Confidence Interval (CI) estimate…

A

Range or interval of values for parameters with a level of confidence attached (95% confidence that the interval contains the parameter)

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4
Q

Why are confidence ‘intervals’ also called ‘confidence interval estimates’?

A

Because the method used to calculate confidence intervals is an estimation.

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5
Q

Why Confidence Interval Estimate vs. Point Estimate?

A

Generally, point estimates are not accurate enough to provide information about the parameter, or the variability within the parameter.

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6
Q

Estimation uses sample data to generate ________ in the population.

A

Parameters

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7
Q

Do the properties of CLT hold if the population is normally distributed and the population is > 30?

A

Yes

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8
Q

95% confidence interval means that

A

We are 95 % confident that interval contains mew

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9
Q

When Student’s t Distribution?

A
  1. Distribution not normal
  2. n < 30
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10
Q

What type of sample is used in confidence interval calculations?

A

Random sample is preferred.

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11
Q

Measurements of sample population are called _________.

A

Parameters.

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12
Q

What is Statistical Inference?

A

Process of reaching a conclusion about a population based on information from a sample of that population

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13
Q

What is mu1 - mu2?

A

Difference in means

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14
Q

In CI >= 30 formula, what are:

X bar,

Z,

s, and

n?

A

X bar = Point Estimate

Z = value from Z table

s = standard deviation

n = sample size

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15
Q

What is Sp?

A

Pooled Estimate of Common Standard Deviation

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16
Q

What is mud?

A

Mean difference

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17
Q

How do you calculate confidence interval?

A

CI = point estimate +- margin of error

Point Estimate = X bar

Margin of Error = (Z*(s/(square root of ‘n’)))

therefore,

CI = X bar +- (Z*(s/(square root of ‘n’)))

*Z or t value, based on sample size*

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18
Q

When do you use the CI estimation for mud?

A
  1. When you have a continuous outcome, and
  2. When you have two matched/paired samples,
  3. Unit of analysis is a pair
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19
Q

When do you use the CI estimation for mu?

A
  1. When you have a continuous outcome, and
  2. When you have a single sample, and
  3. When you want to estimate for the population mean for that sample.
20
Q

Do the properties of CLT hold true if sample is < 30 and normally distributed?

A

Yes.

21
Q

What is formula for CI for mud?

A

Xbard = Σ(x1 - x2)/n

22
Q

In confidence interval estimates, _____________ gives the range of values above and below the ___________.

A

margin of error

point estimate

23
Q

Can you use t distribution for large n?

A

Yes, because when n is large, t is approximately equal to standard normal distribution (Z).

24
Q

The words ______ and ______ clues that we’re calculating Mean Difference.

A

before, after

pre, post

25
Q

To get a smaller interval, do what?

A

Either lower level of confidence or increase n.

26
Q

Measurements of sample data are called ____________.

A

Statistics

27
Q

Types of Stastical Inference

A
  1. Estimation
  2. Hypothesis Testing
28
Q

Confidence Interval (formula)

A

CI = Point Estimate ± Margin of Error

29
Q

Disadvantages of using t-distribution to calculate confidence intervals:

A
  1. Wider intervals
  2. Must be able to assume that the underlying distribution is normal.
30
Q

Why Student’s t Distribution?

A
  1. n < 30
  2. Cannot use z distribution b/c CLT does not hold
  3. Sample point estimates may not be reliable estimate of true population values
31
Q
A
32
Q

Is the point estimate representative of the entire population?

A

No. It is based on one sample and does not consider the variability within the parameter.

33
Q

Explain mean difference.

A

Mean difference computes the mean (average) of differences between pre and post values. Measurements are dependent.

Mean difference = Σ(Xa - Xb)/n

Ex. BMI study…pre BMI (X1a), post BMI (X1b),

sum of differences divided by n

34
Q

Mu, which represents the mean of the population is a __________.

Parameter or Stastic

A

Parameter

35
Q

Estimation determines

A

likely values for an unknown population parameter.

36
Q

What is best single estimator for parameter (e.g., mean)?

A

Point estimate

37
Q

In CI < 30 formula, what are:

X bar,

t,

s,

n?

A

X bar = Point Estimate

t = value from t table

s = standard deviation

n = sample size

38
Q

True or False: There will always be some degree of uncertainty when you caculate point estimates based on your sample.

A

True

39
Q

Sample statistics are analyzed to…

A

support or reject the hypothesis about the parameter.

40
Q

Which is better? Confidence Interval or Point Estimate.

Why?

A

Confidence Interval Estimates

Generally, point estimates are not accurate enough to provide information about the parameter, or the variability within the parameter.

41
Q

Do the properties of CLT hold if the population is not normally distributed and < 30?

A

No.

42
Q

What can be said about the sample drawn from the population in both

estimation and hypothesis testing?

A

The sample is random

43
Q

When estimating difference in means, what is formula for Point Estimate?

A

mu1 - mu2

44
Q

Explain difference of means.

A

Mean of all pre measurements - Mean of all post measurements

Measurements are independent.

Ex. Pre BMI (X1a), Post BMI (X1b)

(Xbara - Xbarb)

45
Q

Key Points (3) of Student’s t Distribution?

A
  1. It is a set of distributions, not a single distribution. Collectively, these sets assume the shape of a bell shaped curve.
  2. Uses the parameter, degrees of freedom (df)

df = n-1

  1. If n is sufficiently large, student’s distribution (t) is approximately equal to standard distribution (z)
46
Q

X bar, represents the sample mean of a __________.

Parameter or Stastic

A

Statistic

47
Q

Do the properties of CLT hold true if the population < 30 and normally distributed?

A

Yes.

MHA622 - Biostatistics (4 decks)

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