20 Questions

Statistical Questions to Ask

Strategic questions that help you understand data, statistics, and research findings, covering methodology, interpretation, and implications to help you make informed decisions based on evidence.

1

What is the sample size of this study, and how was it selected?

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Why this works

Helps you understand the scope and representativeness of the data, which is crucial for assessing the reliability and generalizability of the findings.

2

What is the margin of error for these statistics, and how confident can we be in the results?

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Why this works

Gives you insight into the precision of the data and helps you understand the level of uncertainty in the statistical findings.

3

What methodology was used to collect this data, and are there any potential biases?

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Why this works

Reveals the data collection process and helps you understand potential sources of bias that could affect the validity of the results.

4

How do these statistics compare to previous studies or historical data?

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Why this works

Provides context for the findings and helps you understand whether the results are consistent with other research or represent a change.

5

What are the key variables in this analysis, and how are they defined and measured?

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Why this works

Clarifies the scope of the analysis and helps you understand what factors are being examined and how they're being assessed.

6

What statistical tests were used to analyze this data, and are they appropriate for the research question?

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Why this works

Reveals the analytical approach and helps you understand whether the statistical methods are suitable for the type of data and research question.

7

What are the limitations of this study, and what conclusions can we safely draw?

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Why this works

Identifies the boundaries of the research and helps you understand what can and cannot be concluded from the data.

8

How do these statistics account for different demographic groups or populations?

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Why this works

Explores the representativeness of the data and helps you understand whether the findings apply to different groups or populations.

9

What is the correlation between different variables, and does correlation imply causation?

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Why this works

Clarifies the relationships between variables and helps you understand the difference between correlation and causation.

10

How do these statistics handle outliers or extreme values, and what impact do they have?

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Why this works

Reveals how unusual data points are treated and helps you understand their influence on the overall results.

11

What is the confidence interval for these statistics, and what does it tell us about the range of possible values?

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Why this works

Provides information about the precision of the estimates and helps you understand the range of possible values for the population parameter.

12

How do these statistics account for different time periods or trends over time?

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Why this works

Explores the temporal aspects of the data and helps you understand whether the findings are stable or changing over time.

13

What are the assumptions underlying this statistical analysis, and are they reasonable?

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Why this works

Reveals the theoretical foundations of the analysis and helps you understand whether the statistical approach is appropriate for the data.

14

How do these statistics handle missing data or incomplete information?

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Why this works

Explores data quality issues and helps you understand how gaps in the data are addressed and their potential impact on the results.

15

What is the effect size of these findings, and is it practically significant?

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Why this works

Clarifies the magnitude of the effects and helps you understand whether the findings are meaningful in real-world terms.

16

How do these statistics account for different geographic regions or locations?

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Why this works

Explores the spatial aspects of the data and helps you understand whether the findings apply across different locations.

17

What are the potential confounding variables in this analysis, and how are they controlled?

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Why this works

Identifies other factors that might influence the results and helps you understand how they're accounted for in the analysis.

18

How do these statistics handle different measurement scales or units of analysis?

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Why this works

Explores the measurement aspects of the data and helps you understand how different scales or units are handled in the analysis.

19

What is the statistical power of this study, and is it sufficient to detect meaningful effects?

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Why this works

Reveals the study's ability to detect effects and helps you understand whether the sample size is adequate for the research question.

20

What questions do you have for me about my understanding of these statistics, and what would you like me to clarify?

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Why this works

Shows your engagement and interest in the data while giving you insight into what the analyst values in statistical communication.

How to Understand and Interpret Statistics

Expert tips and techniques for getting the most out of these questions.

Best Practices

Ask About Methodology

Focus on questions that help you understand how the data was collected and analyzed to assess the quality and reliability of the findings.

Understand Context and Limitations

Ask about the scope, limitations, and context of the statistics to understand what conclusions can and cannot be drawn.

Explore Relationships and Causation

Ask questions that help you understand the relationships between variables and whether correlation implies causation.

Question Sequences

The Methodology Sequence

1
What is the sample size of this study?
2
What methodology was used to collect this data?
3
What are the limitations of this study?

The Analysis Sequence

1
What statistical tests were used to analyze this data?
2
What is the correlation between different variables?
3
What is the effect size of these findings?

Common Pitfalls

Don't Assume Causation

Understand that correlation does not imply causation and ask questions that help you distinguish between the two.

Don't Ignore Context

Ask questions that help you understand the context and limitations of the statistics rather than taking them at face value.

Don't Overlook Methodology

Focus on understanding how the data was collected and analyzed rather than just the final numbers.

Conversation Templates

The Methodology Explorer

1
Step 1: Start with: "What is the sample size of this study?"
2
Step 2: Follow with: "What methodology was used to collect this data?"
3
Step 3: Conclude with: "What are the limitations of this study?"

The Analysis Framework

1
Step 1: Begin with: "What statistical tests were used to analyze this data?"
2
Step 2: Explore with: "What is the correlation between different variables?"
3
Step 3: End with: "What is the effect size of these findings?"

Further Reading

"The Statistical Thinking Guide" by Sarah Myers
"How to Interpret Statistics" by Jennifer Smith
"The Complete Guide to Data Analysis" by Michael Johnson

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