Quantitative Research Flashcards
Chapter 3.1
Studies human behavior and mental processes by seeking causal relationships among variables, by gathering quantifiable data, and by performing statistical analyses.
Quantitative research
In quantitative research, the method of selecting the sample is
dependent on the purpose and nature of the study.
Participants are deliberately selected from a variety of levels (strata) or subgroups within the population.
Stratified sampling
Sampling technique in which every member of the population has an equal chance of being chosen to participate in the study.
Random sampling
Techniques for random sampling
Table of random numbers, lottery, and fish bowl.
Is a non-probability sampling technique where participants are selected based on the convenience of the researcher.
Convenience sampling
Participants are purposely selected based on particular characteristics.
Purposive sampling
Quanti: Two main types of statistical analysis:
Descriptive and Inferential statistics
used to describe the basic features of the data in a study.
Descriptive statistics
What are the statistics that provide basic summaries about the sample and the variables?
Frequencies, percentages, means, and standard deviations
Used to draw inferences or conclusions about associations between variables.
Inferential
Used to measure the relationship between two variables.
Correlation
A statistical technique that is so widely used in quantitative research.
Pearson Product Moment Correlation
Statistical tests that can be used to analyze the differences among means.
T-TEST AND ANOVA (ANALYSIS OF VARIANCE)
Is the way data is collected, organized, interpreted, and shown in order to find patterns and trends. It uses statistical methods to make sense of data, helping people make informed decisions and test hypotheses. This analysis can describe data or make predictions about a bigger group based on a smaller sample.
Statistical Analysis
Used to describe the basic features of the data in a study. Such as frequencies, percentage, means, and standard deviations are used to provide basic summaries about the sample and the variable.
✧ Purpose: Summarizes and describes data.
✧ Scope: Focuses on the dataset at hand.
✧ Outcome: Provides insights into characteristics of the data.
✧ Example: Average tests scores of a class
Descriptive Statistics
Used to draw inferences or conclusions about associations between variables. Employs statistical techniques to test hypotheses and estimate parameters, helping to generalize findings beyond the immediate data set.
✧ Purpose: Makes predictions or generalizations about a population.
✧ Scope: Extends findings to a larger population.
✧ Techniques Used: Hypothesis testing, confidence intervals, regression.
✧ Outcome: Offers conclusions about a population based on sample data.
✧ Example: Predicting future sales based on a sample’s data.
Inferential Statistics
is used to measure the relationship between two variables. It reveals how closely two variables vary together and so how well one predicts the other.
Correlational Research
is a statistical technique that is so widely used in quantitative research. The result of correlational analysis is a number called a correlation coefficient.
Pearson Product-Moment Correlation
What does positive correlation mean?
When value of one variable increases, so will the second variable.
What does negative correlation mean?
When value of one variable increases, the values of second variable decreases.
What does 0 correlation mean?
There is no linear correlation.
is used to compare the means between two groups. To determine if they are significantly different from each other or if a treatment has an effect.
T-test
Use when comparing from the same group at different times or conditions (within-subjects design).
Paired t-test
