🚀 Data Analyst Interview Questions with Answers — Part 5

📊 Descriptive Statistics & EDA

41. What are mean, median, and mode?
📌 Mean → Average value of data
Mean = Sum of all values / Number of values

📌 Median → Middle value when data is sorted

📌 Mode → Most frequently occurring value

These measures help summarize data quickly.

42. What is standard deviation and variance?
📌 Variance measures how far data points spread from the mean.

📌 Standard Deviation is the square root of variance and shows data variability in the same unit as the data.

Low standard deviation → data points are close to the mean.
High standard deviation → data points are more spread out.

43. What are quartiles and IQR?
📌 Quartiles divide data into four equal parts.
• Q1 → 25th percentile
• Q2 → Median (50th percentile)
• Q3 → 75th percentile

📌 IQR (Interquartile Range) measures the spread of the middle 50% of data.
IQR = Q3 - Q1

IQR is commonly used to detect outliers.

44. How do you detect outliers and what should you do with them?
Outliers are unusual data points that differ significantly from other observations.

Common detection methods:
✔️ Boxplots
✔️ Z-score
✔️ IQR method

Possible actions:
📌 Remove incorrect data
📌 Investigate business reasons
📌 Transform data if needed
📌 Keep them if they are valid business cases

45. What is a distribution and how do you inspect it?
A distribution shows how data values are spread.

Common ways to inspect distributions:
📊 Histograms
📊 Boxplots
📊 Density plots

These help analysts understand patterns, skewness, and variability.

46. What is skewness and kurtosis?
📌 Skewness measures asymmetry in data distribution.
• Positive skew → Tail on the right
• Negative skew → Tail on the left

📌 Kurtosis measures how heavy or light the tails of a distribution are compared to normal distribution.

These metrics help understand data behavior.

47. How do you calculate growth rate, percentage change, and CAGR?
📌 Percentage Change Formula:
Percentage Change = (New Value - Old Value) / Old Value * 100

📌 CAGR (Compound Annual Growth Rate):
CAGR = (Ending Value / Beginning Value)^(1/n) - 1
Where n = number of years

These metrics are widely used in finance and business performance tracking.

48. How do you compute cohort-style metrics?
Cohort analysis groups users based on a shared characteristic such as signup month.

Example:
📌 Retention rate by signup month
📌 Revenue by customer acquisition month

It helps businesses analyze user behavior over time.

49. How do you summarize categorical vs numerical data?
📌 Categorical Data → Summarized using counts, percentages, and frequency tables.
Examples:
✔️ Gender
✔️ Country
✔️ Product Category

📌 Numerical Data → Summarized using statistical measures.
Examples:
✔️ Mean
✔️ Median
✔️ Standard deviation
✔️ Minimum and maximum values

50. How do you structure an EDA notebook or report?
A good EDA structure usually includes:

1️⃣ Business problem statement
2️⃣ Data overview
3️⃣ Data cleaning steps
4️⃣ Missing-value analysis
5️⃣ Outlier detection
6️⃣ Univariate and bivariate analysis
7️⃣ Visualizations
8️⃣ Key insights and recommendations

Well-structured EDA improves clarity and collaboration.

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