midterm Flashcards
measurement process
concept, idea or construct> measure > observe idea empirically
quantitative researcher go deductive; qualitative researcher go inductive
measurement process, conceptualization
-process of specifying what we mean when we use particular terms
-taking an construct/idea and giving it a conceptual theoretical definition, a good definition has a clear, explicit meaning
measurement process, operationalization
-defining variables into measurable factors
validity
In social research, an indicator is valid if it measures the concept it intends to measure
content validity
asses whether a test is representative of all aspect of the construct
face validity
considers how suitable the content of a test seems to be on the surface. It’s similar to content validity, but face validity is a more informal and subjective assessment, “face value”
criterion validity
-Evaluates how closely the results of your test correspond to the results of a different test.
-To evaluate criterion validity, you calculate the correlation between the results of your measurement and the results of the criterion measurement. If there is a high correlation, this gives a good indication that your test is measuring what it intends to measure.
construct validity
evaluates whether a measurement tool really represents the thing we are interested in measuring. A construct refers to a concept or characteristic that can’t be directly observed, but can be measured by observing other indicator that are associated with it
reliability
consistency, quality of measuring an instrument that would produce same values in repeated observations
test-retest reliability
measures the consistency of results when you repeat the same test on the same sample at a different time. You use it when you are measuring something that you expect to stay consistent in your sample
interrater interobserver reliability
interrater reliability measures the degree of agreement between different people observing or assessing the same thing.
then you calculate the correlation between their different sets of results. If all the researchers give similar ratings, the tests has a higher interrater reliability
parallel forms reliability
measures the correlation between two equivalent versions of a test. You use it when you have two different assessment tools or sets of questions deigned to measure the same thing.
internal consistency
internal consistency assesses the correlation between multiple items in a test that are intended to measure the same construct.
You can calculate internal consistency without repeating the test or involving other researchers, so its a good way of assessing reliability when you only have one data set.
primary research
-primary research refers to research that has involved the collection of original data specific to a study
-PR is often carried out with the goal of producing new knowledge
-researcher aim the answer unanswered question or questions that have not bee asked
secondary research
-SR involves the summary or syntheses of the data and lit the has been written by others
Concept
an abstract idea(s), notion, plan
Theory
statement or set of statements describing
relationships among concepts
Nominal Level of Measurement
-The first level of measurement is nominal level of measurement. In this level of measurement, the numbers in the variable are used only to classify the data. In this level of measurement, words, letters, and alpha-numeric symbols can be used.
-Qualitative/Categorical
-Names, Colors. Gender, Labels
-Order does not matter
Ordinal
-The ordinal level of measurement groups variables into categories, just like the nominal scale, but also conveys the order of the variables. For example, rating how much pain you’re in on a scale of 1-5, or categorizing your income as high, medium, or low.
-ranking placement
-order matters
-differences cannot be measured
Interval Level of Measurement
-The interval level is a numerical level of measurement which, like the ordinal scale, places variables in order. Unlike the ordinal scale, however, the interval scale has a known and equal distance between each value on the scale (imagine the points on a thermometer).
-the order matters
-differences can be measured
-no true “0” starting point
Ratio Level of Measurement
-The ratio level of measurement is an extension of the interval level of measurement. It deals with data that have a natural zero point. The difference between the values, and the ratio of values, both are meaningful in the ratio level of measurement.
-the order matters
-differences are measurable
-contains a “0” starting point
Variable
-Element, feature or factor that is
liable to change.
-The ability to take on two or
more values.
Dependent
Variable
the variable you are trying to
Explain
Independent Variable
the variable hypothesized to “cause” or lead to, or explain variation in another variable
simple hypothesis
shows a relationship between one dependent variable and a single independent variable
example-“If you eat more vegetables, you will lose weight faster.”
complex hypothesis
shows the relationship between two or more dependent variables and two or more independent variables
example- “Eating more vegetables and fruits leads to weight loss, glowing skin, and reduces the risk of many diseases such as heart disease.”
directional hypothesis
shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature.
example- “children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal.”
discrete variable
A set of data is discrete if the values belonging to the set are distinct and separate ex number of children
continuous variable
A set of data is said to be continuous if the values in the set can take on any value within a finite or infinite interval ex height of a child
non directional hypothesis
It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.
null hypothesis
It’s a negative statement, and there is no relationship between independent and dependent variables.
Associative hypothesis
Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable.
causal hypothesis
causal hypothesis proposes a cause and effect interaction between two or more variables.
p-value
The p-value is the probability of obtaining results as extreme or more extreme than the ones observed given the null hypothesis is true
Compare p-value to level of significance, α (alpha)
if p ≤ α: Reject H0
if p > α: Fail to Reject H0
Theory
Statement or set of statements describing relationship among concepts
Concept
An abstract idea, notion, plan
Variable
Element feature or factor that is liable to change
Descriptive statistics
Summarizing information into logical and practical manner
Camparitive satistics
Comparing 2 different samples in order to determine where differences are
Correlational statistics
Comparing 2 statistics to determine if there is a relationship between them
