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Critical Inquiry > Exam 3 > Flashcards

Exam 3 Flashcards

1
Q

What are the uses of statistics in research?

A
  • Provide a description of the research sample (descriptive statistics)
  • Perform statistical tests of significance on research hypotheses (inferential statistics)
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2
Q

What do descriptive characteristics characterize?

A
  • Shape
  • Central tendency (averages)
  • Variability
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3
Q

What do descriptive statistics do?

A

*Provide a description (“picture”) of the dataset
Include
–frequency distributions
–measures of central tendency
–measures of variability
*These statistics illustrate the characteristics of a sample
–allow comparison of the sample to other samples

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4
Q

What does a table of rank ordered scores do?

A

*Shows how many times each value occurred (frequency)

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5
Q

What is a histogram?

A
  • A bar graph
  • -composed of a series of columns
  • -each representing a score or class interval
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6
Q

What is a normal distribution? (bell shaped)

A
  • Most scores fall in the middle
  • Fewer scores found at the extremes
  • Symmetrical
  • Mean, median and mode represent the same value
  • Important assumption for parametric statistics
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7
Q

What is a skewed distribution?

A
  • asymmetrical
  • to the right or left
  • distribution of scores above and below the mean are not equivalent
  • there are specific statistics appropriate to non-normal distributions
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8
Q

What is a positive skew?

A
  • Skewed to the right (tail points to the right)
  • Most scores cluster at low end
  • Few at high end
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9
Q

what is a negative skew?

A
  • Skewed to the left (tail points to the left)
  • Most scores at the high end
  • Few at low end
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10
Q

What is mode?

A

Score that occurs most frequently

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11
Q

What is median?

A

Value above which there are as many scores as below

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12
Q

What is the mean?

A

Sum of scores divided by number of scores

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13
Q

How do you measure variability?

A
  • Range
  • Percentiles; quartiles
  • Variance
  • Standard Deviation
  • Coefficient of variation
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14
Q

What is range?

A

Difference b/w highest and lowest values in the distribution

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15
Q

What is percentile?

A

Percentage of a distribution that is below a specified value

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16
Q

What is variance?

A

Measure of variability in a distribution, equal to the square of the standard deviation

17
Q

What is standard deviation?

A

Descriptive statistic reflecting the variability or dispersion of scores around the mean

18
Q

What is coefficient of variation?

A

Measure of relative variation as a %

—(SD/mean) *100

19
Q

What is a standardized score?

A

*Expresses scores in terms of standard deviation units

20
Q

What is inferential statistics?

A
  • Decision making process

* Estimate population characteristics from data from a sample

21
Q

What is statistical inference?

A
  • Draw valid conclusions from research data
  • –Does the sample represent the population?
  • Probability and sampling error
22
Q

What is probability?

A
  • Likelihood an event will occur given all possible outcomes
  • p represents probability e.g. p=0.50 that a coin flip will be heads
  • Used in research to make decisions about how well sample data estimates characteristics of a population
  • Did differences we see b/w treatment groups occur by chance or are we likely to see these differences in the larger population?
  • Estimating what would happen to others based on what we observe in our sample
23
Q

What is sampling error?

A
  • Estimating population characteristics (parameters) from sample data
  • -Assumes that samples are random i.e. individuals randomly drawn from the population
  • -And that samples represent the population
  • Sampling error: sample values and population values differ
24
Q

Give an example of sampling error

A
  • *Say there are 1000 000 people over the age of 55 years in the population with population mean age of 67 and SD of 5.2 years
  • We randomly select 15 people and find that mean age is 62 yrs and SD is 2.7
  • A second sample of 15 people might have age of 73 and SD of 6.4
  • -i.e. means and SD will very likely differ with each time we sample
25
Q

What is the sampling error for a single sample?

A
  • Sampling error of the mean for a single sample is sample mean (Xbar) minus population mean (µ)
  • If drew many (infinite) samples would see varying degrees of sampling error
26
Q

What would the plot of sample means be?

A
  • The shape of a normal curve
  • -Mean of all sample means will equal population mean
  • The distribution of sample means is called a “sampling distribution of means”
  • Predictable properties of normal curve
  • –use the concept of the “sampling distribution” to draw inferences from sample data
27
Q

What is standard error of the mean?

A
  • Sampling distribution is a normal curve
  • -Can establish its variability
  • Standard deviation of sampling distribution of means is called standard error of the mean (SEM)
  • –Estimate of population standard deviation

*SEM = SD/√n, where SD=sample SD and n=sample size

28
Q

What is a confidence interval?

A
  • Can use sample mean as an estimate of population mean
  • -Point estimate
  • -Single sample value will not be a true estimate of population mean
29
Q

What is the interval estimate of mean?

A
  • Interval which contains the population mean
  • Range of values which contain the population mean
  • –Confidence interval (CI)
30
Q

What are the ranges of scores of CI?

A
  • -Boundaries (confidence limits)
  • -Contains the population mean
  • Boundaries based on sample mean and SEM
  • Expressed as 95% confidence interval
  • CI= X ± Z (SEM) where z=1.96
  • “We are 95% confident that the population mean falls within this range of values.”
31
Q

What is a null hypothesis?

A
  • No difference

* H0: μA = μB

32
Q

What is an alternative hypothesis?

A
  • Is a difference

* H1: μA ≠ μB

33
Q

What are hypothesis testing based on?

A
  • Your statistical tests are based on the null hypothesis only: rejecting or failing to reject H0
  • If p ≤ 0.05, we reject the null hypothesis and accept the alternative hypothesis
  • If p > 0.05, we fail to reject the null hypothesis
34
Q

What is hypothesis direction?

A
  • Directional vs. Non-directional alternative hypothesis
  • -Non-directional do not specify which group will be greater in value than the other
  • —-E.g. H1: μA ≠ μB Population A will have different strength to Population B (greater or lower not specified)
  • -Directional specifies which group will be greater than the other
  • —-E.g. H1: μA > μB Population A will have greater strength than Population B

Critical Inquiry (3 decks)

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