research methods 2

Question 1

what do statistics allow us to do?

Answer 1

summarize, interpret, and present collected data

Question 2

descriptive statistics

Answer 2

present information abt data at a glance to give us an overall idea abt experiment

Question 3

measures of central tendency

Answer 3

mean, median, mode

Question 4

ways to visually summarize data

Answer 4

• pie graphs
• bar graphs
• diagrams (i.e. venn)

Question 5

histogram

Answer 5

• type of graph
• reports number of times groups of values appear in a data set
• x-axis is groups of values called bins
• y-axis measures number of values in dataset that fall into each bin (frequency)

Question 6

what are histograms used for?

Answer 6

as a base to create a frequency distribution

Question 7

frequency distribution

Answer 7

• type of graph
• illustrates distribution of how frequently values appear in a data set
• smooth curve tht connects peak of each bar in histogram

Question 8

how are many everyday measures distributed?

Answer 8

normal distribution

Question 9

normal distribution

Answer 9

• smooth
• bell-shaped
• symmetrical around a single peak

Question 10

what do measures of central tendency tell us?

Answer 10

• where a dataset is centered
• most common is the mean

Question 11

mean

Answer 11

• average
• add together all points in a dataset, divide by number of items

Question 12

what is the mean susceptible to?

Answer 12

influence by outliers

Question 13

outliers

Answer 13

extreme points distant form others in the dataset

Question 14

mode

Answer 14

• value that appears most frequently in a set
• tells us the most typical response
• only one that can be used for non-numerical datasets

Question 15

median

Answer 15

• center value in a dataset when arranged numerically
• if even, mean of center points is used
• tells us middle of dataset

Question 16

advantage of median

Answer 16

can’t be pulled in one direction by an outlier

Question 17

what do measures of central tendency not tell us?

Answer 17

values that fall around the center point

Question 18

measures of variability

Answer 18

• review spread and distribution of a dataset
• most common is standard deviation

Question 19

groups of descriptive statistics

Answer 19

• measures of central tendency
• measures of variability

Question 20

standard deviation

Answer 20

• measure of the average distance of each data point from the mean
• larger deviation = data more spread out

Question 21

inferential statistics

Answer 21

statistics that allow us to use results from samples to make inferences about overall underlying populations

Question 22

what do the distributions look like when you’re testing an experimental and control group?

Answer 22

• positive effect: two distributions exist bc you have diff. populations (one is shifted on x-axis)
• negative effect: same distribution bc. both groups in same pop’n

Question 23

how do we determine if shift in distribution btwn groups was bc of random variation or actual correlation?

Answer 23

T-test

Question 24

T-test

Answer 24

• statistical test
• considers each data point from both groups to calculate probability that two samples were drawn from the same population
• produces a P-value

Question 25

P-value

Answer 25

- got from T-test - probability (0-1) indicating likelihood of difference being observed even if no "rea'" difference exists - probability of getting same results even if hypothesis is wrong - "is the difference large enough btwn groups to attribute results to hypothesis?"

Question 26

what P-value represents results that are statistically significant?

Answer 26

- 0.05 - less than 5% chance tht observed difference was bc of chance - 95% chance that a difference btwn groups does exist

Question 27

statistical significance

Answer 27

- when the diff btwn two groups is bc of a true difference btwn properties of two groups, not bc of random variation - type 1 and type 2 errors can occur

Question 28

type 1 and type 2 errors

Answer 28

- type 1: believing a difference exists when it doesn't (false alarm) - type 2: failing to see a difference when it does exist (miss)

Question 29

what makes it difficult for scientists to perform experiments?

Answer 29

ethical and practical concerns

Question 30

what can scientists do to avoid ethical concerns in experiments?

Answer 30

observational studies

Question 31

observational studies

Answer 31

- observe effect of particular variable without performing explicit manipulations - experimental design principles can apply here (i.e. hypothesis/data)

Question 32

correlation

Answer 32

- measure of the strength of the relationship btwn two variables - symbolized by correlation coefficient

Question 33

correlation coefficient

Answer 33

- R - btwn -1 and +1 - tells us strength and direction of correlation

Question 34

meaning of correlation coefficient

Answer 34

+1: perfect positive correlation -1: perfect negative correlation close to 0: weaker correlation

Question 35

relationship between slope of trend line and R-value

Answer 35

- none - as long as points are on trend line, R-val is +/-1 - slope can be wtvr - if trendline is horizontal, R-val is 0 (no correlation)

Question 36

correlation doesn't equal causation

Answer 36

- even if strong correlation exists, we can't say relationship btwn variables is causing an effect - mb bc of confounding variables