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52 Cards in this Set
- Front
- Back
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· Operational definitions·
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OD means how the researcher decides to measure the variables in a study; defining in terms that are observable countable measurable the instrument should be both reliable and valid |
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Reliabilityo
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The extent to which a measure, procedure or instrument yields the same result on repeated trials.
Do you get similar results with multiple measures? Do other people get similar results using the same measurements? |
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Inter-rater reliabilityo
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The extent to which two or more individuals agree. It addresses the consistency of the implementation of a rating system.
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Repeated measures·
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Using the same measurement instrument to measure the same things over and over again.
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Validityo
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The degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
Are you measuring what you say you’re measuring? if you are: valid. If you’re not: low validity |
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Internalvalidity
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Deals with the issue of causation, the rigor with which the study was conducted and the extent to which the designers of a study have taken into account alternative explanations such as: external factors, maturation, testing effect, multiple instruments used.
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Threats to internal validityo
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Are there external factors in the world affecting results? Maturation- tests of same subjects over time might just be measurable natural changes of the subjects over time.
Testing effect- the more often you give the same test, your subjects become acclimated to it. Instrumentation: When you change instruments |
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Externalvalidity o
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The extent to which the results of a study are generalizable or transferable
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Constructvalidityo
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Seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
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Facevalidity o
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How a measure or procedure appears.
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Socialvalidity·
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Acceptability of the intervention you have designed to use on the population. Acceptability of the methods you are using to administer that test on the people. Raises the question of culturally sensitive research.
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Survey Constructiono
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Instructions are clear and concise and simple.
Avoid bias. Questions are mutually exclusive and exhaustive. Closed ended questions cover all possibilities. One answer per question. |
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Double-barreled questionso
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when someone asks a question that touches upon more than one issue, yet allows only for one answer.
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Issues related to mutual exclusivenesso
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Making sure that the same answer doesn't appear in two places. For example where you select from a range: 1 to 5 5 to 10 11 to 15 16 to 20 5 appears in two places |
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Issues related to exhaustiveness·
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Making sure your instrument allows all available answers for example: |
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Population vs. Sample·
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The population is the entire set under consideration.
Samples are drawn from populations. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. |
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Distributionso
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The range of values of a particular variable.
Normal distribution: both ends of the curve equal. positive skew: long end on the right. negative skew: long end on the left. Bimodal distribution: two modes |
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Scatterplotso
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a graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.
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Histograms and bar graphso
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histogram: a diagram consisting of rectangles whose area is proportional to the frequency of a variable and whose width is equal to the class interval.
bar graph: a diagram in which the numerical values of variables are represented by the height or length of lines or rectangles of equal width. |
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Normal curveo
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both ends of the curve equal.
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Skewnesso
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positive skew: long end on the right.
negative skew: long end on the left. |
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Bimodal (and, by implication, multimodal)distributions·
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Bimodal distribution: two modes
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Basic Descriptive Statisticso
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Used to describe things: Describe the sample, the responses, and maybe the population.
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Rangeo
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The difference between the highest and lowest scores in a distribution.
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Means, medians, and modeso
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Measures of central tendency. Mean: The average score within a distribution. (ratio: arithmetic average) Median: The center score in a distribution. (ordinal data) Mode: The most frequent score in a distribution. (nominal data) |
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Standard deviation·
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A measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution.It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
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Correlationo
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A non-cause and effect relationship between two variables.
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Independent and dependent variableso
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Independent V: A variable that is part of the situation that exist from which originates the stimulus given to a dependent variable. Includes treatment, state of variable, such as age, size, weight, etc.
Dependent V: A variable that receives stimulus and measured for the effect the treatment has had upon it. |
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Pearson’s r (the correlation coefficient)o
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A measure of the direction of the relationship between independent and dependent variables and the strength of that relationship.
7 or higher= very strong positive relationship. -0.7 or lower- very strong negative relationship |
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Coefficient of determinationo
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Coefficient of Determination = r(squared)if r=0.6 then r2=0.36
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Necessary conditions for causation·
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1) temporal requirements: cause before effect.
2) empirical correlation between the variables. 3) there cannot be a third variable that can explain the variable between the first two |
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Simple Regressiono
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In simple linear regression, we predict scores on one variable from the scores on a second variable. The variable we are predicting is called the criterion variable and is referred to as Y. The variable we are basing our predictions on is called the predictor variable and is referred to as X.
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Three elements of a regression equationo
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The equation of a straight line. y = mx + b
Y is the equation mx is the slope times the x intercept b is the y intercept. |
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Least squares estimate of a “best fit” line· Hypothesis Testingo
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A line of best fit is a straight line that is the best approximation of the given set of data.
Step 1: Calculate the mean of the x-values and the mean of the y-values. Step 2: Find the slope. Step 3: Find the y intercept. Step 4: use the slope and the y intercept to form the equation of the line (y = mx + b) |
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Null hypothesiso
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there is no statistically significant difference between the two groups
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Alternative hypothesiso
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Ha1: There is a statistically significant difference between the two groups; Two tailed test
Ha2: The mean score for a particular group will be higher than the other group; one tailed test |
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Type I and Type II errors·
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a type I error is the incorrect rejection of a true null hypothesis (a "false positive"),
while a type II error is the failure to reject a false null hypothesis (a "false negative"). |
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Samplingo
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Sampling is the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen.
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Assumption of a normal distribution andrandomnesso
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each random variable has the same probability distribution as the others and all are mutually independent.
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Simple probability theory as it relates tosampling·
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A probability sampling method is any method of sampling that utilizes some formof random selection. In order to have a random selection method, you must set upsome process or procedure that assures that the different units in your population haveequal probabilities of being chosen.
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Significance Testingo
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The significance level for a given hypothesis test is a value for which a P-value less than or equal to is considered statistically significant. Typical values for are 0.1, 0.05, and 0.01. These values correspond to the probability of observing such an extreme value by chance.
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Importance of the significance levelo
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If the probabilityis less than or equal to the significance level, then the nullhypothesis is rejected and the outcome is said to bestatistically significant. Traditionally,experimenters have used either the 0.05 level (sometimes called the 5%level)
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T-Testo
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A T-test is a test that you use when you are testing the statistical significance between the mean scores of two groups.
A t-test is used to determine if the scores of two groups differ on a single variable. For instance, to determine whether writing ability differs among students in two classrooms, a t-test could be used. |
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One-way ANOVAo
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Analysis of Variance. used to determine differences among the means of two or more groups on a variable.
One-way ANOVA is a technique used to compare means of three or more samples (using the F distribution). This technique can be used only for numerical data. |
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Two-way ANOVAo
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examines the influence of two different categorical independent variables on one continuous dependent variable. The two-way ANOVA not only aims at assessing the main effect of each independent variable but also if there is any interaction between them.
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Chi-square
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relating to or denoting a statistical method assessing the goodness of fit between observed values and those expected theoretically.
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Quantitative Data:
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nominal (categorical)Names of things can be separated into mutually exclusive categories ordinal have to be in a certain order high to low, or low to high interval no absolute zero thermometer example= zero does not mean “nothing” ratio there is an absolute zero speedometer= zero literally means zero. there is no motion
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nominal
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(categorical) Names of things can be separated into mutually exclusive categories. You cannot have a mean for categorical data
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ordinal
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have to be in a certain order high to low, or low to high interval no absolute zero thermometer example= zero does not mean “nothing”
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ratio
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there is an absolute zero speedometer= zero literally means zero. there is no motion You cannot have a mean for categorical data
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Discrete data
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whole numbers- no values in between each data
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Continuous data
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On an infinite continuum
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