Research Methods
Module 1:
Scientific Method
Used to ensure reliable and meaningful research
A standardized process to minimize biases, conflicts and oversights
Scientific Method Steps
Theory
Theory - A general set of ideas about how the world works
Research past works
Hypothesis
Hypothesis - Testable statements making specific predictions about relationships between variables
Research Methods
How the hypothesis is tested
Collect Data
Measure outcomes
Analyze Data
Discover trends/relationships between variables
Report Findings
Publish articles in scholarly journals
Revise Theories
Incorporate new information into our understanding of the world
Paradigm Shift - A particularly dramatic change in our way of thinking
Conducting an Experiment
Anecdotal Evidence - evidence gathered from others/ones’ experiments
Hearsay
Personal experiences
Not sufficient for Science
Experiment - measure the effect of 1 variable on another
Independent Variable - manipulated by the scientist
Dependent Variable - being observed by the scientist
Control Groups
Experimental and control groups should be as similar as possible
Experimental Group - the independent variable IS manipulated
Control Group - the independent variable IS NOT manipulated
Within-Participant Design - manipulating the independent variable WITHIN each participant
Between-Participants Design - 1 experimental and 1 control group
Practice Effect - improvement over time(the course of the experiment) from experience
Ard to separate from the multiplication of the independent variable
Confounding Variables - Variables that obscure the effects of the independent variable on the dependent variable
Any variable related to the independent variable
Leads to questionable results
Makes it difficult to draw conclusions
Sampling
Sampling tries to eliminate all confounding variables
But it is difficult to find people who fit ALL the requirements
Results from very specific groups CAN NOT be generalized to other groups
Population - A general group of people we want to learn about
Sample - subset of individuals selected from the population
Random Assignment - Participants are randomly assigned control or experimental group
Random Sample - A group of participants selected from a larger population where everyone has an equal chance of being chosen
Most representative of the real population to avoid biases
Happens after random assignment
If both random assignment and sampling are truly random, we are reasonably confident that any pre-existing differences are limited
Avoiding Biases and Placebo Effect
Placebo Effect - An individual shows a response to a treatment that has no therapeutic effects
Participant Bias - Intentionally or unintentionally bias their results to match expected results
Experimental Bias - Intentionally or unintentionally influencing results to favour their hypothesis
Experimenter Bias - actions by the experimenter, intentionally or unintentionally, that influence the results
Blinding - A research method that conceals information to prevent bias in an experiment, ensuring more accurate results
Blind Experiment - Participants don’t know the group they are in or the treatment they are receiving
Minimizes participant bias
Double Blind Experiment - neither the experimenter nor the participants know what group they are in
Minimizes experimenter bias
Module 2:
Histogram - A type of graph that reports the number of times bins appear in a data set
Base for frequency distribution graph
Bins - Groups of values
Frequency Distribution - Illustrating the distribution of how frequently values appear in a data set
The line shows how likely something is to occur in the distribution
Normal Distribution Characteristics
Smooth
Symmetrical
Bell-shaped
Curve with a single peak
Every day measures are normally distributed
E.g. IQ, Height, Test scores
Measures of Central Tendency
Measures of Central Tendency - where a data set is centred
Mean - the average value of a data set
Add all data points, then divide by the number of data points
Can be shewed by outliers
Outlier - extreme point, distant from other data points
Mode - value that appears most frequently in a set
The typical response
Can be used for mom-muberical data sets
Median - The center value in a data set when arranged numerically
Not shewed to 1 side
Only focus on the center/typical value → ignoring other data points
Measure of Variability
Standard Deviation - A measure of the average distance of each data point from the mean
If we only used measures of central tendency, both examples would be the same
Smaller spread = smaller standard deviation
Larger spread = larger standard deviation
Inferential Statistics
Inferential Statistics - use data sets to make inferences about the overall population
T-Test - uses data points from both experimental and control groups to calculate the probability that samples are from the same population
Produces a P-Value
P-Value - probability of the T-Test
From 0-1
Is the difference large enough?
Statistically significant is <0.05
Less than 5% that is the difference between the groups, is by chance
Statistical Significance - when the difference between 2 groups is due to some TRUE difference between the properties of the groups, it IS NOT due to random variation
Types of Errors
Type 1: False Alarm - believing there is a difference when a difference DOESN’T exist
Type 2: Miss - Failing to see a difference when a difference DOES exist
Observational Research
Used when it is difficult or impossible for scientists to perform experiments
E.g. Ethical or practical concerns
Principles of experimental design also apply to observational research
Correlation - a measure of the strength and direction of the relationship between variables
How close are data points to the trend line?
Correlation Coefficient (r) - indicates the strength and direction of correlation
from -1 to 1
NOT RELATED TO SLOPE
Correlation DOES NOT EQUAL Causation
Strength = the number
How far the number is from 0 on either side
Direction = the sign
= Positive
= Negative