Business statistics means applying statistical tools to collect, summarize, analyze and interpret business data for decision making.
Scope (exam points):
Importance:
Types:
Quantitative further:
A frequency distribution groups data into classes and shows frequencies.
Key terms:
CF helps find median and quartiles for grouped data.
Central tendency describes a typical/central value.
Mean = (Sum of observations)/n
Merits: simple, uses all values. Demerit: affected by extreme values.
Median is the middle value when data are arranged. Merit: not affected much by extremes.
Mode is the most frequent value. Useful for “most popular size/brand” type decisions.
Mean = Σx / n
Weighted mean = Σ(wx) / Σw Used when items have different importance (quantities, credits).
Mean = Σ(f×m) / Σf where m is class mid-value.
Access the complete note and unlock all topic-wise content
It's free and takes just 5 seconds
From this topic
Sum = 10+12+14+14+20 = 70. Mean = 70/5 = 14.
Ordered data: 10,12,14,14,20. Median = 14 (middle). Mode = 14 (highest frequency).
Business mathematics are mathematics used by commercial enterprises to record and manage business operations. Commercial organizations use mathematics in accounting, inventory management, marketing, sales forecasting, and financial analysis.
Download this note as PDF at no cost
If any AD appears on download click please wait for 30sec till it gets completed and then close it, you will be redirected to pdf/ppt notes page.
Business statistics means applying statistical tools to collect, summarize, analyze and interpret business data for decision making.
Scope (exam points):
Importance:
Types:
Quantitative further:
A frequency distribution groups data into classes and shows frequencies.
Key terms:
CF helps find median and quartiles for grouped data.
Central tendency describes a typical/central value.
Mean = (Sum of observations)/n
Merits: simple, uses all values. Demerit: affected by extreme values.
Median is the middle value when data are arranged. Merit: not affected much by extremes.
Mode is the most frequent value. Useful for “most popular size/brand” type decisions.
Mean = Σx / n
Weighted mean = Σ(wx) / Σw Used when items have different importance (quantities, credits).
Mean = Σ(f×m) / Σf where m is class mid-value.
Steps:
Mode = L + [(f1 − f0) / (2f1 − f0 − f2)] × h Where:
Dispersion shows how spread out data are.
Range = Max − Min Simple but depends only on extremes.
QD = (Q3 − Q1)/2 Less affected by extremes.
For ungrouped data:
For grouped data, use f weights: Variance = Σf(x − mean)^2 / Σf
Interpretation: higher SD means more variability/risk.
CV compares variability across series with different means: CV = (SD/Mean) × 100
Lower CV → more consistency/stability.
Correlation measures direction and degree of relationship between two variables.
Pearson correlation coefficient r lies between −1 and +1.
(At basics, focus on interpretation rather than heavy computation.)
Regression estimates one variable based on another.
Regression lines are best-fit lines.
Business use: predict sales from advertising, demand from price, etc.
Data: 10, 12, 14, 14, 20 Mean = (10+12+14+14+20)/5 = 70/5 = 14
Ordered data: 10, 12, 14, 14, 20 Median = 14 (middle) Mode = 14 (most frequent)
Data: 2, 4, 6 Mean = 4 Deviations: −2, 0, +2 Squares: 4, 0, 4 ⇒ sum = 8 Variance = 8/3 = 2.667 SD = √2.667 ≈ 1.633
Tip: In answers, write formula first, then substitute.
If these notes helped you, a quick review supports the project and helps more students find it.
Measures of central tendency show a representative or central value of a dataset.
Arithmetic Mean: Mean = Σx / n Merits: simple, uses all values. Demerits: affected by extreme values.
Median: Median is the middle value after arranging data. Merit: not much affected by extreme values; useful for skewed data.
Mode: Mode is the most frequently occurring value. Useful in business to find most popular size/brand or most demanded item.
Thus mean, median and mode help summarize data into one typical value for comparison and decisions.