Hypothesis Testing in Statistics

Definition: A systematic process used to test a hypothesis to determine whether it is true or false
Types of Hypothesis:
- Null Hypothesis (H0): a hypothesis that states there is no significant difference or relationship
- Alternative Hypothesis (H1): a hypothesis that states there is a significant difference or relationship
Steps in Hypothesis Testing:
1. State the null and alternative hypotheses
2. Choose a significance level (α)
3. Select a test statistic and determine the critical region
4. Collect and analyze data
5. Calculate the p-value
6. Make a decision: reject or fail to reject the null hypothesis
Error Types:
- Type I Error: rejecting a true null hypothesis
- Type II Error: failing to reject a false null hypothesis

Types of Data Analysis:
- Descriptive Analysis: summarizes and describes the basic features of the data
- Inferential Analysis: uses sample data to make inferences about a population
Data Visualization:
- Types: tables, graphs, charts, plots
- Purpose: to communicate data insights and patterns
Statistical Analysis:
- Measures of Central Tendency: mean, median, mode
- Measures of Variability: range, variance, standard deviation
- Correlation and Causation: examining relationships between variables

Importance: ensures that research is conducted in a responsible and respectful manner
Key Principles:
- Respect for Human Dignity: protecting participants' autonomy, privacy, and well-being
- Beneficence: maximizing benefits and minimizing harm
- Justice: fair distribution of benefits and burdens
- Informed Consent: obtaining participants' voluntary and informed consent
Ethical Issues:
- Confidentiality and Anonymity
- Deception and Debriefing
- Participant Selection and Sampling

Definition: a research design that involves manipulating one or more variables and measuring their effect on a dependent variable
Types of Experimental Designs:
- Between-Subjects Design: each participant is assigned to only one condition
- Within-Subjects Design: each participant is exposed to all conditions
- Mixed Design: combination of between- and within-subjects designs
Key Elements:
- Independent Variable: the variable being manipulated
- Dependent Variable: the variable being measured
- Control Group: a group that does not receive the treatment
- Experimental Group: a group that receives the treatment

Definition: a research method that involves collecting data through self-report measures
Types of Surveys:
- Cross-Sectional Survey: collects data from a sample at one point in time
- Longitudinal Survey: collects data from a sample over a period of time
- Panel Survey: collects data from the same sample at multiple points in time
Survey Administration:
- Self-Administered Surveys: participants complete the survey on their own
- Interviewer-Administered Surveys: a researcher or interviewer asks the questions
- Online Surveys: surveys administered through the internet or email
Survey Design Considerations:
- Question Wording and Ordering
- Response Format and Scales
- Survey Length and Fatigue

Hypothesis: a systematic process used to test a hypothesis to determine whether it is true or false
Null Hypothesis (H0): states there is no significant difference or relationship
Alternative Hypothesis (H1): states there is a significant difference or relationship
Steps in Hypothesis Testing:
- State the null and alternative hypotheses
- Choose a significance level (α)
- Select a test statistic and determine the critical region
- Collect and analyze data
- Calculate the p-value
- Make a decision: reject or fail to reject the null hypothesis
Error Types:
- Type I Error: rejecting a true null hypothesis
- Type II Error: failing to reject a false null hypothesis

Data Analysis Types:
- Descriptive Analysis: summarizes and describes the basic features of the data
- Inferential Analysis: uses sample data to make inferences about a population
Data Visualization: communicates data insights and patterns
- Types: tables, graphs, charts, plots
Measures of Central Tendency:
- Mean: the average value of a dataset
- Median: the middle value of a dataset
- Mode: the most frequent value in a dataset
Measures of Variability:
- Range: the difference between the largest and smallest values
- Variance: the average of the squared differences from the mean
- Standard Deviation: the square root of the variance

Importance: ensures that research is conducted in a responsible and respectful manner
Key Principles:
- Respect for Human Dignity: protecting participants' autonomy, privacy, and well-being
- Beneficence: maximizing benefits and minimizing harm
- Justice: fair distribution of benefits and burdens
- Informed Consent: obtaining participants' voluntary and informed consent
Ethical Issues:
- Confidentiality and Anonymity: maintaining participants' privacy
- Deception and Debriefing: using deception in research and debriefing participants
- Participant Selection and Sampling: selecting participants and sampling methods

Definition: a research design that involves manipulating one or more variables and measuring their effect on a dependent variable
Experimental Design Types:
- Between-Subjects Design: each participant is assigned to only one condition
- Within-Subjects Design: each participant is exposed to all conditions
- Mixed Design: combination of between- and within-subjects designs
Key Elements:
- Independent Variable: the variable being manipulated
- Dependent Variable: the variable being measured
- Control Group: a group that does not receive the treatment
- Experimental Group: a group that receives the treatment

Definition: a research method that involves collecting data through self-report measures
Survey Types:
- Cross-Sectional Survey: collects data from a sample at one point in time
- Longitudinal Survey: collects data from a sample over a period of time
- Panel Survey: collects data from the same sample at multiple points in time
Survey Administration:
- Self-Administered Surveys: participants complete the survey on their own
- Interviewer-Administered Surveys: a researcher or interviewer asks the questions
- Online Surveys: surveys administered through the internet or email
Survey Design Considerations:
- Question Wording and Ordering: careful wording and ordering of survey questions
- Response Format and Scales: selecting response formats and scales
- Survey Length and Fatigue: minimizing survey length and fatigue