Exam 2: Quantitative Data Collection and Analysis

Question 1

descriptive statistics

Answer 1

• summarize or describe data

- reduce large sets of data into meaningful pieces

Question 2

inferential statistics

Answer 2

• draw conclusions about a population based on data from sample
• looks at differences between groups

Question 3

correalational statistics

Answer 3

• strength of relationship between two variables

Question 4

what is quantitative data analysis

Answer 4

• process of organizing data to draw conclusions

Question 5

how is data in descriptive statistics displayed?

Answer 5

• through frequency distribution

Question 6

what is frequency distribution in descriptive statistics?

Answer 6

• a table or figure that shows number of data observations that fall into specific intervals
• histograms, pie charts, line charts, table

Question 7

What is a measure of central tendency?

Answer 7

• it describes the center point of data using a single value

- mean, median, mode

Question 8

what is a measure of variability/ measure of data dispersion

Answer 8

• describes how far a data set has strayed away from the mean
• standard deviation

Question 9

mean

Answer 9

average of adding all values and dividing

Question 10

median

Answer 10

middle score

Question 11

mode

Answer 11

most frequently occurring

Question 12

Normal distribution of central tendency

Answer 12

• smooth bell shape curve

- mean, median mode are same value

Question 13

skewness

Answer 13

• negative is skewed left

- positive is skewed right

Question 14

range

Answer 14

difference between highest and lowest score (11 - 4 = 7)

Question 15

variance

Answer 15

reflects variation of distribution within set of scores; used to calculate standard deviation

Question 16

standard deviation

Answer 16

spread the data of the mean; square root of variance

- most commonly used measure of variance

Question 17

empirical rule

Answer 17

if distribution scores follow a bell-shaped curve we would expect 68% in 1 SD, 95% within 2 SD, 99.7% within 3 SD.

Question 18

Descriptive statistics is split into what 2 categories?

Answer 18

• central tendency (mean, median, mode)

- variability (standard deviation, range)

Question 19

one tailed hypothesis test

Answer 19

• directional test
• research suspect intervention is better, sets up hypotheses to reject null hypothesis
• mean 1 greater or less than mean 2

Question 20

two tailed test

Answer 20

• non-directional test
• consider either possibility
• null hypothesis rejected if result fails at either tail
• mean 1 not equal to mean 2

Question 21

what is probability (p-value)

Answer 21

• significance level ( denoted by alpha)

Question 22

what does low probability (p-value) indicate? less than .05

Answer 22

• lower chance to find effect due to chance
• probability of found different due to chance is low
• reject null hypothesis

Question 23

Type I error

Answer 23

• error created by rejection null hypothesis when it is true

- test that shows patient has disease but really doesn’t

Question 24

Type II error

Answer 24

• accepting null hypothesis when its false

- blood test failing to test for disease when disease is present

Question 25

Student t-test (independent t-test)

Answer 25

• used when there is no relationship between two groups

Question 26

paired t -test

Answer 26

• used when groups are same

- compares pre and post test of same individuals

Question 27

analysis of variance (ANOVA)

Answer 27

• test difference between two means
• computes multiple t-test at one time and tells you if there is difference between groups
• compares within group difference between group difference

Question 28

post-hoc analysis

Answer 28

• after ANOVA, this tells us which groups differ from one another on which specific variables
• tukey scheffe and duncan adjustments test

Question 29

parametric data

Answer 29

samples that assume normal distribution (bell curve)

• have homogenous variance
• continuous data i.e. weight

Question 30

non-parametric data

Answer 30

• samples that do not have homogenous variance
• does not follow normal distribution
• nominal (chi square), ordinal scale (mann-whitney U)

Question 31

Chi-square test

Answer 31

• non parametric statistic
• analyzes frequencies or proportions
• sum of differences rather than expectations
• one tailed test
• coin toss

Question 32

correlation coefficient

Answer 32

• strength of relationship bt two variables
• no cause - effect can be inferred
• ranges from +1.0 to -1.0; 0 shows no relationship

Question 33

Know degrees of correlation: strong positive, strong negative, weak positive, weak negative, etc..

Answer 33

visualize it!

Question 34

correlational statistics relationship test: person r test

Answer 34

used with parametric data

Question 35

correlational statistics relationship test: spearman rank-order correlation coefficeint

Answer 35

• used with non-parametric data

Question 36

regression analysis - predictive values

Answer 36

• as one variable increases predict increase in other variables

Question 37

simple regression

Answer 37

examine relationship bt dependent and independent variable

Question 38

multiple regression

Answer 38

used when there is more than one independent variable

Question 39

factor analysis

Answer 39

• identification of factors that compose a construct
• group items together to create a factor
  i. e. sensory profile

Question 40

considering how to choose the right statistic

Answer 40

• consider research question
• how many groups compared
• simplest way to understand data

Question 41

Ratio

Answer 41

• continuous
• numeric
• can take any value
• height, weight, age

Question 42

Interval

Answer 42

• discrete
• countable
• ordered numeric; no smooth value to value transition
• # of students, # of strokes

Question 43

Ordinal

Answer 43

• Categorical
• Natural order
• Education Level, socioeconomic status

Question 44

Nominal

Answer 44

• Categorical
• No natural order
• Gender, Ethinicity