3. Statistics
Statistics is the branch of mathematics that involves
collecting, organizing, analyzing, interpreting, and
presenting data. It helps in making informed decisions by
summarizing information, identifying patterns, and drawing
conclusions from data.
4. Example of Statistics in Action
Scenario: A teacher wants to analyze the heights of 5 students to understand the
average height of students in the class
Step 1: Collecting Data
The teacher collects the heights of 5 students:
Heights (in centimeters):
150, 160, 155, 170, 165
5. Student ID Year level Score
1 2nd 150
2 2nd 160
3 2nd 155
4 2nd 170
5 2nd 165
Step 2: Organizing Data
The teacher organizes the data into a table:
6. Step 3: Analyzing Data
Mean (Average):
To find the mean height, the teacher adds all the heights and
divides by the number of students.
Mean
150+ 160+ 155+170+165
5
800
5
160
So, the mean height is 160 cm.
The median is the middle value when the data is ordered
Ordered Heights: 150, 155, 160, 165, 170
The median height is the middle value:
Median = 160 cm
7. Step 4: Interpreting the Data
• The mean height is 160 cm, which means the average height of the
students is 160 cm.
• The median height is also 160 cm, showing that the middle student in
terms of height is 160 cm.
• Since both the mean and median are the same, it suggests the data is
fairly evenly distributed.
8. The role of Statistics in decision-making
Understanding Statistics: What & Why
9. Statistics play a critical role in decision-making by providing
valuable insights and data-driven evidence that help individuals
and organizations make informed choices.
The role of Statistics in decision-making
10. Statistics help identify patterns or trends in data, which can guide
decisions. For example, analyzing sales data over time can reveal
whether a product is gaining popularity, enabling businesses to
decide whether to continue production, adjust marketing
strategies, or introduce new features
1. Understanding Trends and Patterns
12. Descriptive Statistics
Descriptive statistics are used to summarize and describe the main
features of a dataset. This type of statistic helps to provide a clear and
simple overview of the data, often through numerical measures and
visualizations.
Key Elements:
• Measures of Central Tendency (e.g., Mean, Median, Mode) that summarize the central
point of the data.
• Measures of Dispersion (e.g., Range, Variance, Standard Deviation) that describe the spread
or variability in the data.
• Charts and Graphs (e.g., Histograms, Pie Charts, Bar Graphs) that visually represent data to
make patterns easier to see and understand.
13. Inferential Statistics
Inferential statistics are used to make predictions or generalizations about a
population based on a sample of data. This type of statistics helps to make
decisions or inferences about a larger group from a smaller, manageable
subset of data.
Key Elements:
• Hypothesis Testing: Testing an assumption (e.g., whether a new teaching method improves
student performance).
• Confidence Intervals: Estimating the range in which a population parameter (like the mean)
lies.
• Regression Analysis: Predicting a variable (e.g., sales, stock prices) based on another
variable (e.g., advertising spend).
14. Commonly Used Tools
Excel is one of the most popular tools for both descriptive and inferential
statistics due to its user-friendly interface and built-in statistical functions.
15. Using statistical models, decision-makers can make predictions
about future events or behaviors. For example, a company might
use statistical analysis to predict the future performance of a
product or market based on historical data
2. Predicting Future Outcomes
16. Statistics allow organizations and individuals to make decisions
based on objective data rather than intuition or guesswork. This
approach increases the likelihood of making the best decision.
3. Making Data-Driven Decisions
17. Statistics help assess the risk and uncertainty of different
decisions. By analyzing data and probabilities, decision-makers
can choose options that minimize risks and maximize potential
rewards.
4. Evaluating Risks
18. Statistics are useful when comparing different options or
alternatives. By analyzing data from different scenarios, decision-
makers can assess the advantages and disadvantages of each
option.
5. Comparing Alternatives
19. In industries such as manufacturing, statistics are used to
monitor production processes, ensuring quality control and
identifying areas for improvement.
6. Quality Control and Improvement
21. Statistics plays a crucial role in Information Technology (IT) by providing the
tools and methods to analyze, interpret, and make sense of data. In today’s
data-driven world, IT relies heavily on statistics to improve decision-making,
optimize systems, and enhance user experiences
22. Real-World Applications of Statistics
• Healthcare and Medicine
• Business and Marketing
• Sports
• Education
• Government and Public Policy
• Environmental Science
• Finance and Economics
• Transportation and Logistics
24. What are the role of Application in Statistics?
1. Data Collection
Survey Tools: Applications like Google Forms, SurveyMonkey, and
Qualtrics assist in designing surveys, collecting responses, and
managing data.
Data Logging: Sensors and IoT devices collect real-time data, which is
essential for time-series analysis.
Mobile Apps: Applications help gather data in remote locations or from
specific demographics through user-friendly interfaces
25. What are the role of Application in Statistics?
2. Data Management
Storage: Applications like Microsoft Excel, Google Sheets, and databases
such as MySQL and PostgreSQL manage large datasets efficiently.
Data Cleaning: Tools automate error correction, handle missing data,
and prepare datasets for analysis.
26. What are the role of Application in Statistics?
3. Visualization
Charts and Graphs: Tools like Tableau, Power BI, and Matplotlib
(Python) create visual representations of data to identify trends and
patterns.
Interactive Dashboards: Applications enable dynamic and interactive
visualizations for real-time data interpretation
27. Fields to Apply Statistics
ECONOMICS BUSINESS BANKING
ASTRONOMY
NATURAL AND
SOCIAL SCIENCE MATHEMATICS
ACCOUNTING
MANAGEMENT AND
ADMINISTRATION
28. In Business, has many important uses :
1. To make reliable forecasts about business activities
2. To improve business processes
3. To summarize business data
4. To draw conclusion business data
In Economics
1. Economist use statistics to collect information analyze data
and test hypotheses
Relationship between supply and demand and import
and exports are found using statistical information
29. In Accounting
1. It involves mostly basic arithmetic operations, but when it comes to creating
reports, statistics play as key role.
In Banking
1. Bankers use statistics approaches to estimate the number of
people who will be making deposits compared to the number
of people requesting
