Quantitative Data Analysis

Question 1

what are the two levels statistical analysis?

Answer 1

descriptive
inferential

Question 2

what is descriptive statistical analysis used for?

Answer 2

used to summarize the data

Question 3

what is inferential statistical analysis used for?

Answer 3

used to draw conclusions about population parameters based on data from a sample

Question 4

what are types pf descriptive measurements?

Answer 4

frequency distribution
measures of central tendency
measures of dispersion/variability

Question 5

what is frequency distribution?

Answer 5

Frequency distribution in research is a way of organizing and summarizing data to understand patterns or trends within a dataset. It involves grouping data into categories or intervals and counting the number of observations that fall into each category.

Question 6

what is measures of central tendency?

Answer 6

statistical tools used to describe the center or average of a dataset. (mean, median, mode)

Question 7

what are measures of dispersion?

Answer 7

statistical tools used to describe the spread or variability of a dataset. They help researchers understand how spread out the values are from the central tendency measures
ex: standard deviation, range

Question 8

what are distributions for statistics?

Answer 8

normal
T
skewed

Question 9

what is a normal distribution?

Answer 9

a specific pattern that many natural phenomena tend to follow when measured. It’s often called a “bell curve” because when graphed, it forms a symmetrical, bell-shaped curve

Question 10

what is T-distribution?

Answer 10

a probability distribution that is similar to the normal distribution but is used when the sample size is small or when the population standard deviation is unknown.

Question 11

what is skewed distribution?

Answer 11

a distribution of data that is asymmetrical, meaning it is not evenly balanced around its central value. Instead, the data is stretched out more to one side than the other

Question 12

what are examples of measures of association?

Answer 12

correlation coefficient
Spearman Rank Correlation
Odds ratio/relative risk

Question 13

what is correlation coefficient?

Answer 13

a numerical measure that describes the strength and direction of the relationship between two variables. It tells us how much and in what way two variables change together.

Question 14

what is spearman rank correlation?

Answer 14

a statistical method used to measure the strength and direction of the relationship between two variables. It’s specifically designed to assess the association between variables when the data is not normally distributed or when the relationship is non-linear.

Question 15

what is odds ratio/relative risk?

Answer 15

relationship between two
categorical variables

Question 16

what data is spearmans rank correlation used with?

Answer 16

ordinal data

Question 17

what is ANOVA?

Answer 17

a statistical test used to compare the means of
two or more independent samples (using the F distribution)

Question 18

what are hypotheses?

Answer 18

Predictions the researcher makes about the expected relationships

Question 19

what is the intent of hypotheses?

Answer 19

reject the null hypothesis, thus proving the alternative
hypothesis

Question 20

what determines whether a null hypothesis can be rejected?

Answer 20

statistical significance

Question 21

what is a p value?

Answer 21

a measure of the probability that an observed
difference could have occurred just by random chance

Question 22

what does a lower p value mean?

Answer 22

the greater the statistical
significance of the observed difference

Question 23

what does a P less than .05 mean?

Answer 23

regarded as unlikely enough to reject the null hypothesis, it is “statistically significant at the 0.05 or 5%
level”

Question 24

what does a p value greater than .05 mean?

Answer 24

not enough evidence to reject the null hypothesis,
“statistically non-significant

Question 25

sample size needed to test ta hypothesis depends on what 4 factors?

Answer 25

1. expected difference between two groups
2. Variability of the data
3. Power of the study = probability that any difference is real
   (usually at least 80%)
4. Level of significance accepted (usually 5%)