Nur 200 EXAM 2 Questions with Verified
Correct Answers
Levels of measurement from lowest to highest
nominal -> ordinal -> interval -> ratio
nominal
You can count, but not order or measure, the lowest form
Nominal characteristics
- data categories must be exclusive
- data categories must be exhaustive
Ex. Gender, race/ethnicity, colors, etc.
Ordinal
values can be ranked but not measured
Ordinal characteristics
- categories must be exhaustive and mutually exclusive
- each category must be recognized as higher or lower or better or worse than another
category
- You do not know exactly how much higher or lower one subject's score is in relation to
another subject's score
Nonparametric or Distribution-free analysis techniques
used to analyze nominal and ordinal level variables to examine relationships
Nonparametric or Distribution-free analysis techniques assumptions
,- values need not be normally distributed
- the level of measurement is usually ordinal or nominal
measurement of central tendency
mean, median, mode
Measurement of central tendency for NOMINAL level data
mode (most frequently occurring in a data set)
Measurement of central tendency for ORDINAL level data
median (middle value in a data set)
Interval
The distances between intervals of the scale are numerically equal
Interval characteristic
- There is no absolute zero
- The score of zero does not indicate that the property being measured is absent
- continuous variable
Ex. temperature (Celsius)
Ratio
The highest form of measurement
ratio characteristics
- numerically equal intervals of a scale
- There is an absolute zero
, - continuous variables
Ex. Pulse, blood pressure, age
parametric statistics
Analysis techniques conducted on interval and ratio levels of data to describe variables,
examine relationships among variables, and determine dthe ifference between groups
parametric statistics assumptions
- distribution of scores is expected to be a normal distribution or approximately normal
- variables are continuous, measured at the interval or ratio level
- data can be treated as though they were obtained from a random sample
Significant Results
results that align with the outcomes predicted by the researcher and their team
How are significant results identified
by * or p values that are less than or equal to 0.05
Measures of Dispersion
Descriptive statistical techniques are conducted to identify the individual differences of the
scores in a sample, the dispersion or spread around the mean, and the extent to which
individual scores deviate from one another
What does it mean if a sample is homogeneous?
The scores are similar with little variation. (close to each other)
What does it mean if a sample is heterogeneous?
Correct Answers
Levels of measurement from lowest to highest
nominal -> ordinal -> interval -> ratio
nominal
You can count, but not order or measure, the lowest form
Nominal characteristics
- data categories must be exclusive
- data categories must be exhaustive
Ex. Gender, race/ethnicity, colors, etc.
Ordinal
values can be ranked but not measured
Ordinal characteristics
- categories must be exhaustive and mutually exclusive
- each category must be recognized as higher or lower or better or worse than another
category
- You do not know exactly how much higher or lower one subject's score is in relation to
another subject's score
Nonparametric or Distribution-free analysis techniques
used to analyze nominal and ordinal level variables to examine relationships
Nonparametric or Distribution-free analysis techniques assumptions
,- values need not be normally distributed
- the level of measurement is usually ordinal or nominal
measurement of central tendency
mean, median, mode
Measurement of central tendency for NOMINAL level data
mode (most frequently occurring in a data set)
Measurement of central tendency for ORDINAL level data
median (middle value in a data set)
Interval
The distances between intervals of the scale are numerically equal
Interval characteristic
- There is no absolute zero
- The score of zero does not indicate that the property being measured is absent
- continuous variable
Ex. temperature (Celsius)
Ratio
The highest form of measurement
ratio characteristics
- numerically equal intervals of a scale
- There is an absolute zero
, - continuous variables
Ex. Pulse, blood pressure, age
parametric statistics
Analysis techniques conducted on interval and ratio levels of data to describe variables,
examine relationships among variables, and determine dthe ifference between groups
parametric statistics assumptions
- distribution of scores is expected to be a normal distribution or approximately normal
- variables are continuous, measured at the interval or ratio level
- data can be treated as though they were obtained from a random sample
Significant Results
results that align with the outcomes predicted by the researcher and their team
How are significant results identified
by * or p values that are less than or equal to 0.05
Measures of Dispersion
Descriptive statistical techniques are conducted to identify the individual differences of the
scores in a sample, the dispersion or spread around the mean, and the extent to which
individual scores deviate from one another
What does it mean if a sample is homogeneous?
The scores are similar with little variation. (close to each other)
What does it mean if a sample is heterogeneous?
