Research Methods

Question 1

Three steps of statistical process

Answer 1

1) collect data (e.g., surveys), covered in Lesson 2; (2) describe and summarize the distribution of the values in the data set; (3) interpret by means of inferential statistics and statistical modeling, i.e., draw general conclusions

Question 2

Quantitative Variables

Answer 2

variables where the actual numerical value is meaningful. Quantitative variables represent an interval or ratio measurement

Question 3

Qualitative Variables

Answer 3

qualitative variables correspond to nominal or ordinal measurement (zoning classification)

Question 4

Continuous variables

Answer 4

These can take an infinite number of values, both positive and negative, and with as fine a degree of precision as desired. Most measurements in the physical sciences yield continuous variables.

Question 5

Discrete variables

Answer 5

can only take on a finite number of distinct values. An example is the count of the number of events, such as the number of accidents per month. Such counts cannot be negative

Question 6

dichotomous variables

Answer 6

can only take on two values, typically coded as 0 and 1

Question 7

Descriptive Statistics

Answer 7

Describe the characteristics of the distribution of values in a population or in a sample.

Question 8

Inferential Statistics

Answer 8

Use probability theory to determine characteristics of a population based on observations made on a sample from that population.

Question 9

Normal distribution

Answer 9

Normal Distribution is a probability distribution that is symmetrical around the mean. It is bell shaped and when with a standardized relationship between the mean and variance is called a score.
The highest point on a curve with normal distribution is the truest measure of central tendency and will represent the mean, mode, and median.

Question 10

Central tendency

Answer 10

is a typical or representative value for the distribution of observed values. There are several ways to measure central tendency, including mean, median, and mode.

Question 11

Two ways to measure spread around central tendency

Answer 11

Variance and standard deviation. They both are based on the squared difference from the mean, but the standard deviation is the square root of the variance.

Question 12

Coefficient of Variation

Answer 12

measures the relative dispersion from the mean by taking the standard deviation and dividing by the mean.

Question 13

inter-quartile range

Answer 13

This is the difference in value between the 75 percentile and the 25 percentile, i.e., the 1/4 cut-off value and 3/4 cut-off value in a set of ranked values.

Question 14

confidence interval

Answer 14

This constitutes a range around the sample statistic that contains the population statistic with a given level of confidence, typically 95% or 99%.

Question 15

Variance

Answer 15

A variance is a measure of dispersion around the mean. It is calculated as the average of the sum of the squared deviations from the mean.

Question 16

cluster sampling

Answer 16

In cluster sampling, researchers divide a population into smaller groups known as clusters. They then randomly select among these clusters to form a sample.
Cluster sampling is a method of probability sampling that is often used to study large populations,

Question 17

simple random sampling

Answer 17

A simple random sample takes a small, random portion of the entire population to represent the entire data set, where each member has an equal probability of being chosen

Question 18

stratified random sampling

Answer 18

Stratified random sampling is a method of sampling that involves the division of a population into smaller sub-groups known as strata. In stratified random sampling, or stratification, the strata are formed based on members’ shared attributes or characteristics such as income or educational attainment.

Question 19

systematic random sampling

Answer 19

Systematic sampling is a probability sampling method in which a random sample, with a fixed periodic interval, is selected from a larger population. low probability of contaminating data.

Question 20

positive correlation

Answer 20

high values of one variable match high values of the other, and low values match low values

Question 21

negative correlation

Answer 21

high values of one variable match low values of the other, and vice versa