Flow of Data Analysis

Flow of data analysis

1. Formulating a research question

2. data collection

3. data analysis- descriptive statistics

4. data analysis- inferential statistics.

5. discusion

Formulating a research question

You want to have some sort of goal.

What do you want to answer?

Identify you areas of interest.

Do you have an argument

define your central claim or hypothesis.

Ex of research question

How do we explain this social phenomenon?

Why is support for authoritarian leaders increasing?

Alaways make your research question

measurable

Broad research question

big topic

narrowing down

contributing factors

Specific research question

focused question you can actually research

The most important part

Can the research question be answered through data analysis?

Example of a good refined research question

Are individuals who experience loneliness more likely to support

authoritarian figures?

This process is typically included in

• Introduction (establishing research problem)

• Literature Review (situating the question within existing research)

• Hypotheses (developing theoretical arguments)

Not that common in gov. or business reports.

Data collection has two ways

1. use existing dataset

2. Create your own dataset

Examples of existing datasets

• Public data sources: census, FBI crime data, GSS

• Local data: NYC open data, Chicago PD records.

Examples of creating your own dataset

• Conduct a survey

• Use web-scraping to collect online data

• Locate and compile historical records

• Experiments

Designing a survey

Who are your respondents (target of population).

How are they selected? (sampling method).

What are the key variables? What are the survey questions for those variables? How do you operationalize them for measurement?

Descriptive statistics

• Summarizing key variables

• Visualizing associations between variables

Inferential statistics

• Running a regression model

• Generalizing findings from the sample to the population

• Interpreting regression coefficients

Measures for describing variables

Central Tendency

Variability

Central Tendency

Mean, median, mode

Variability

Variance, Standard Deviation, Shape of Distribution

Decriptive statistics and discovering patterns

Descriptive statistics can reveal interesting trends in your data.

Patterns found in this process can inspire new research questions.

Inferential Statistics

Uses advanced statistical methods to identify relationships between

variables and generalize findings beyond the sample.

Which inferential method is commonly used?

Regression Analysis

Regression Analysis

Measures the strength and direction of relationships between variables.

Discusion

1. interpreting your findings.

2. Addressing research limitations.

Interpreting your findings

-Explain the broader meaning of your results.

- Discuss theoretical implications (how your findings contribute to existing research).

- Highlight practical implications (how your findings apply to real-world contexts).

Addressing research limitations

-Consider potential biases in the survey method.

- Reflect on limitations in your research question or methodology.

-Discuss any constraints related to sample size, measurement, or data

Issues in data collection

-Data may not be readily available.

- Survey Method Challenges: Small sample size, Low response rates

- Operationalization Issues: Difficulty in defining and measuring key variables

Challenges in inferential statistics

-Your method may not establish causality (correlation ≠ causation).

- Model assumptions may not hold, affecting validity.

What questions cannot be answered through data analysis?

if something is morally right or wrong.

-Is the death penalty morally justifiable?

- Should the state have the power to take a life?

- Does the death penalty align with societal values and principles of

justice?

Research Questions That Can Be Answered Through Data Analysis

1) Effectiveness

- Does the death penalty deter crime, especially violent crimes like murder?

2) Economic Impact

- What is the financial burden of maintaining death row on taxpayers?

3) Public Opinion

- How do public attitudes toward the death penalty vary across demographic groups

(age, education, political affiliation)?