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Statistical Analysis Excel Template

Perform comprehensive statistical analysis with hypothesis testing, regression models, ANOVA, and descriptive statistics for rigorous data analysis and research validation.


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Unlock Statistical Insights with Professional Data Analysis

Statistical analysis is the foundation of data-driven decision making, providing the tools to test hypotheses, identify patterns, and draw meaningful conclusions from data. Our Statistical Analysis Template offers comprehensive statistical tools for researchers, analysts, and data scientists to perform rigorous statistical analysis.

From descriptive statistics to advanced hypothesis testing, validate your findings with statistical rigor. Built for researchers, analysts, and data scientists, this template helps you analyze data properly, test hypotheses, and ensure statistical validity of your conclusions.

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Comprehensive Hypothesis Testing & Inference

T-Tests & Z-Tests

Perform one-sample, two-sample, and paired t-tests with automatic calculation of test statistics, p-values, and confidence intervals. Conduct z-tests for large samples and known population variance.

Chi-Square Tests

Test for independence and goodness of fit using chi-square analysis. Analyze categorical data relationships and test whether observed frequencies match expected distributions.

ANOVA Analysis

Perform one-way and two-way ANOVA to compare means across multiple groups. Includes post-hoc tests and effect size calculations for comprehensive analysis.

Non-Parametric Tests

Conduct Mann-Whitney U tests, Wilcoxon signed-rank tests, and Kruskal-Wallis tests for data that doesn't meet parametric assumptions. Includes robust statistical alternatives.

Advanced Regression & Correlation Analysis

Linear Regression Analysis

Perform simple and multiple linear regression with automatic calculation of coefficients, R-squared, and statistical significance. Includes residual analysis and diagnostic plots.

Correlation Analysis

Calculate Pearson, Spearman, and Kendall correlation coefficients with significance testing. Create correlation matrices and identify relationships between variables.

Polynomial & Logistic Regression

Fit polynomial regression models for non-linear relationships and logistic regression for binary outcomes. Includes model selection and validation techniques.

Time Series Analysis

Analyze time series data with trend analysis, seasonal decomposition, and autocorrelation functions. Identify patterns and forecast future values.

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Frequently Asked Questions

What sample size do I need for statistical significance?

The template includes power analysis tools to determine required sample sizes for different effect sizes and significance levels. It provides guidance for various statistical tests and research designs.

How do I choose the right statistical test?

The template includes a decision tree and flowchart to help you select the appropriate statistical test based on your data type, sample size, and research questions.

Can it handle non-normal data distributions?

Yes, the template includes normality tests and non-parametric alternatives for when data doesn't meet normal distribution assumptions. It provides robust statistical options.

Does it include effect size calculations?

The template calculates effect sizes (Cohen's d, eta-squared, etc.) for all statistical tests to help interpret the practical significance of your findings beyond statistical significance.

How does it handle missing data?

The template includes missing data analysis tools with options for listwise deletion, pairwise deletion, and imputation methods. It shows the impact of missing data on results.

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Template Generator

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Charts & Graphs

Create stunning, interactive charts that make data clear.

Spreadsheet Assistant

Generate complex formulas, just describe what you need.

Frequently Asked Questions

If you question is not covered here, you can contact our team.

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How do I analyze data?
To analyze spreadsheet data, just upload a file and start asking questions. Sourcetable's AI can answer questions and do work for you. You can also take manual control, leveraging all the formulas and features you expect from Excel, Google Sheets or Python.
What data sources are supported?
We currently support a variety of data file formats including spreadsheets (.xls, .xlsx, .csv), tabular data (.tsv), JSON, and database data (MySQL, PostgreSQL, MongoDB). We also support application data, and most plain text data.
What data science tools are available?
Sourcetable's AI analyzes and cleans data without you having to write code. Use Python, SQL, NumPy, Pandas, SciPy, Scikit-learn, StatsModels, Matplotlib, Plotly, and Seaborn.
Can I analyze spreadsheets with multiple tabs?
Yes! Sourcetable's AI makes intelligent decisions on what spreadsheet data is being referred to in the chat. This is helpful for tasks like cross-tab VLOOKUPs. If you prefer more control, you can also refer to specific tabs by name.
Can I generate data visualizations?
Yes! It's very easy to generate clean-looking data visualizations using Sourcetable. Simply prompt the AI to create a chart or graph. All visualizations are downloadable and can be exported as interactive embeds.
What is the maximum file size?
Sourcetable supports files up to 10GB in size. Larger file limits are available upon request. For best AI performance on large datasets, make use of pivots and summaries.
Is this free?
Yes! Sourcetable's spreadsheet is free to use, just like Google Sheets. AI features have a daily usage limit. Users can upgrade to the pro plan for more credits.
Is there a discount for students, professors, or teachers?
Currently, Sourcetable is free for students and faculty, courtesy of free credits from OpenAI and Anthropic. Once those are exhausted, we will skip to a 50% discount plan.
Is Sourcetable programmable?
Yes. Regular spreadsheet users have full A1 formula-style referencing at their disposal. Advanced users can make use of Sourcetable's SQL editor and GUI, or ask our AI to write code for you.
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Professional statistical analysis tools to validate hypotheses, analyze relationships, and ensure rigorous data analysis.

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