Descriptive Statistics | Tobit Research Consulting
Data Analysis · Step 2

Descriptive
Statistics Made
Clear

Having completed your data entry, the next stage is generating descriptive statistics — the foundation of every meaningful research finding.

Central Tendency
x̄ = Σx / n
Mean — arithmetic average of observations
Variability
σ² = Σ(x−μ)²/N
Variance — spread around the mean
Distribution Shape
γ₁ = μ₃ / σ³
Skewness — asymmetry of distribution
Peakedness
κ = μ₄ / σ⁴
Kurtosis — tail heaviness of distribution

Understanding Descriptive Statistics

Having written a research proposal that detailed how you will analyze data, and having completed your data entry, descriptive statistics is your next critical stage. It leads to the generation of statistics that present a brief description of coefficients within a given dataset.

At Tobit Research Consulting, we ensure you develop a deep understanding of how to generate measures of central tendency — mean, median, and mode — as well as measures of variability including standard deviation, variance, minimum/maximum values, and Kurtosis/Skewness.

During your research proposal writing stage, you identified and justified why and how you would use descriptive statistics. We now help you execute that plan with precision using leading analytical software.

1

Research Proposal

You identify and justify your descriptive analysis plan in the methodology chapter.

2

Data Entry

Raw data is entered accurately into your chosen statistical software.

3

Descriptive Statistics ← You are here

Generate summaries: central tendency, variability, and distribution shape.

4

Inferential Statistics

Draw conclusions and test hypotheses beyond the immediate dataset.

What You Will Learn to Generate

Descriptive statistics summarise and describe the main features of a dataset. We guide you through every measure — what it means, when to use it, and how to interpret it in the context of your research.

Measures of Central Tendency
Central Tendency

Mean

The arithmetic average of all values in a dataset. The most commonly reported summary statistic in quantitative research.

Md
Central Tendency

Median

The middle value when data is ordered. Especially useful for skewed distributions where the mean may be misleading.

Mo
Central Tendency

Mode

The most frequently occurring value. Particularly relevant in categorical data and identifying common responses.

Measures of Variability
σ
Variability

Standard Deviation

Measures the average distance of data points from the mean. A low SD indicates data is clustered closely; high SD indicates wide spread.

σ²
Variability

Variance

The square of the standard deviation, representing total variability in the data. A fundamental component in many inferential tests.

Variability

Min / Max

The smallest and largest values in a dataset. Together they define the range and help detect potential outliers.

Distribution Shape
γ₁
Distribution Shape

Skewness

Measures the asymmetry of the data distribution. Positive skew means a longer right tail; negative skew means a longer left tail.

κ
Distribution Shape

Kurtosis

Describes the “peakedness” or tail heaviness of a distribution. Helps determine whether data approaches normality before inferential testing.

N
Frequency

Frequency Tables

Count and percentage distributions for categorical variables — essential context before any advanced statistical analysis.

Generate Descriptive Statistics Across All Platforms

SP

SPSS

Quantitative

Most widely used among Kenyan postgraduate students for frequency tables and descriptives.

ST

STATA

Quantitative

Powerful summarize commands for econometrics and panel data research.

R

R

Quantitative

Rich packages like psych and Hmisc for comprehensive descriptive output.

EV

EViews

Quantitative

Time-series descriptive statistics for economics and finance dissertations.

Ex

Excel

Universal

Data Analysis Toolpak for quick descriptive summaries and charts.

SA

SAS

Quantitative

Enterprise-grade PROC MEANS and PROC FREQ for large-scale datasets.

ML

MATLAB

Technical

Advanced statistical toolbox for engineering and science-based research.

NV

NVivo

Qualitative

Descriptive summaries for qualitative datasets — themes, codes, and frequencies.

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Students Guided
Masters & PhD
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Software Platforms
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Research Consultancy

Kenya’s Leading Academic Research Consultancy

Tobit Research Consulting is Kenya’s premier academic research consultancy, providing expert support to postgraduate students across Nairobi and beyond.

We specialize in professional thesis writing, SPSS data analysis, and research proposal development for Masters and PhD students. We have successfully guided over 5,000 students from top Kenyan universities to achieve their academic goals.

Research Proposal (Ch. 1–3)
Project / Thesis (Ch. 4–5)
Concept Paper
Article Publication
Conference Paper
Funding Proposals
Data Analysis (SPSS, STATA…)
Data Collection
Independent Study Paper
AI Removal & Paraphrasing

Ready to Master Descriptive Statistics?

Whether you are a student writing your first research proposal or a postgraduate finalizing your thesis, Tobit Research Consulting will guide you through every statistic — step by step.

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