quantitative data analysis

Question 1

descriptive statistics

Answer 1

are summary statistics that allow the researcher to organize data in different ways that give meaning and facilitate insight
can be used to describe the sample
ex mean age, education level, gender

Question 2

inferential statistics

Answer 2

statistics designed to allow inference from a sample statistic to a population parameter
- allows the researcher to estimate how reliably they can make predictions and generalize findings

Question 3

what are the 4 levels of measurement

Answer 3

nominal, ordinal, interval, ratio

Question 4

nominal

Answer 4

• classified in mutually exclusive categories
• no ranking within the categories
  ex: gender, marital status
• mean, mode, frequency of distribution

Question 5

ordinal

Answer 5

• data must be mutually exclusive and exhaustive and is sorted on the relative ranking of variables
  example: education level or a likert scale
• mode, median
• rank order of coefficients, range, percentile

Question 6

interval

Answer 6

mutually exclusive categories, exhaustive categories and ranking order plus the distances between the intervals are numerically equal
- no zero point on the interval scale
ex: temperature
- mean, median and mode
- range, percentile, standard deviation

Question 7

ratio

Answer 7

• highest level of measurement
• mutually exclusive, exclusive and exhaustive categories, ranking order, equal space between intervals and a continuum of values
  ex: weight, length and volume
• absolute zero exists - can be an absence of weight
• mean, median and mode
• range, percentile, standard deviation

Question 8

frequency distribution

Answer 8

the number of times each event occurs is counted and data is then grouped according to categories; the frequency of each group is reported

Question 9

mean

Answer 9

average
calculated by summing values and dividing that sum by the number of values

Question 10

median

Answer 10

the midpoint in a set of values
50% of distribution fall below the median and 50% above the median

Question 11

mode

Answer 11

the most frequently occurring score in the distribution

Question 12

normal distribution

Answer 12

a theoretical concept that observes that interval or ratio data group themselves about a midpoint in a distribution closely approximating the normal curve
- mean, median and mode are equal

Question 13

positive skew

Answer 13

low range mean

Question 14

negative skew

Answer 14

high range mean

Question 15

range

Answer 15

is the difference between the highest and lowest scores
simplest but most unstable measure of variability

Question 16

percentile

Answer 16

is the percentage of cases a give score exceeds
- median is the 50th percentile
- a score in the 90th percentile is only exceeded by only 10% of scores

Question 17

standard deviation

Answer 17

the average amount of variability in a set of scores or the scores average deviation from the mean
- a measure of how dispersed the data is in relation to the mean, calculated using statistical formula
- the average distance from the mean
- low standard deviation = data are clustered around the mean
- a high standard deviation = data are more spread out

Question 18

inferential statistics

Answer 18

combine mathematical processes with logic and allow researchers to test hypotheses about populations by using data obtained from probability samples
purpose:
- to estimate the probability that statistics found in the sample accurately reflect the population parameter
- test a hypothesis about a population

Question 19

parameter

Answer 19

a characteristics of a population
- a well defined set that has specific properties

Question 20

statistic

Answer 20

is a characteristic of a sample and is used to estimate population parameters

Question 21

parametric tests

Answer 21

are statistical procedures that can be used when three assumptions are present
- the sample from the population has a normal distribution
- level of measurement must be interval or rate with a normal distribution
- sample was obtained through a random sampling procedure

Question 22

non-parametric tests

Answer 22

are statistical procedures that can be used when
- the sample from the population does not have a normal distribution
- level of measurement is nominal or ordinal
- sample was obtained through a non-random sampling procedure

Question 23

hypothesis

Answer 23

H1
a formal statement of the expected relationship between 2 or more variables in a specified population

Question 24

null hypothesis

Answer 24

H0
states there is no relationship between the variables being studies, used for testing and interpreting statistical outcomes

Question 25

type I error

Answer 25

rejection of the null hypothesis when it is actually supposed to be retained
- stating a relationship exists when it does not

Question 26

type II error

Answer 26

retaining the null hypothesis when it should be rejected
- can occur if sample is too small
- stating there is no relationship when there is one

Question 27

level of significance or alpha

Answer 27

is the probability of making a type I error
- 0.05

Question 28

statistical significant hypothesis

Answer 28

unlikely that the findings have occurred by chance
- if the alpha is 0.05, then 95% change the researcher will make the correct conclusion

Question 29

practical significance

Answer 29

is the practical value that the study contributes