• what is statistics

• Perspective statistics
• inferential statistics
• Data statistics
• Example of a Quantitative data
• Example of a Qualitative data
• What is population
•what are the different scale of measurement
• what are the different ways/method to collect data

http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html

http://www.merriam-webster.com/dictionary/statistics

thank you so much Ms.Sue :))

• what is statistics:

Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It involves methods for gathering, summarizing, and analyzing data to make inferences or conclusions about a population based on a sample.

• Perspective statistics:

Perspective statistics refers to the way statistics are used in different fields or contexts. For example, statistics can be used in business to analyze sales data, in healthcare to study patient outcomes, or in social sciences to understand trends or patterns in human behavior.

• inferential statistics:

Inferential statistics involves making predictions or inferences about a population based on a sample. It uses probability theory to generalize findings from a subset of the population (sample) to the whole population.

• Data statistics:

Data statistics refers to the process of collecting, organizing, analyzing, interpreting, and presenting data. It involves techniques such as summarizing data using descriptive statistics, making predictions using inferential statistics, and identifying patterns or relationships in data.

• Example of a Quantitative data:

Quantitative data refers to numerical information or data that can be measured objectively. Examples include age, height, weight, income, and test scores.

• Example of a Qualitative data:

Qualitative data refers to non-numerical information or data that cannot be measured objectively. Examples include opinions, preferences, observations, and interview responses.

• What is population:

In statistics, a population refers to the entire group of individuals, items, or events of interest that we want to study or make inferences about. It is often too large or impractical to measure the entire population directly, so a subset called a sample is selected for analysis.

• What are the different scales of measurement:

There are four different scales of measurement: nominal, ordinal, interval, and ratio.

1. Nominal scale: Data is categorized into distinct groups or categories with no inherent order or ranking. Examples include gender, eye color, or favorite color.

2. Ordinal scale: Data is categorized into distinct groups or categories with a specific order or ranking. Examples include ranks in a race (1st, 2nd, 3rd), or satisfaction ratings (poor, fair, good, excellent).

3. Interval scale: Data is measured on a scale where the intervals between values are equal, but there is no meaningful zero point. Examples include temperature measured in Celsius or Fahrenheit.

4. Ratio scale: Data is measured on a scale where the intervals between values are equal, and there is a meaningful zero point. Examples include height, weight, time, or income.

• What are the different ways/methods to collect data:

There are several methods to collect data, depending on the nature of the study and the research objectives. Some common methods include:

1. Surveys or questionnaires: Participants respond to a set of questions either in person, through mail, phone, or online.

2. Observations: Researchers directly observe and record data without direct interaction with participants.

3. Experiments: Researchers manipulate variables and measure the effects on the outcome of interest.

4. Interviews: Researchers engage in face-to-face or structured conversations to collect data through questions.

5. Existing data: Researchers analyze pre-existing datasets from sources such as government databases, academic institutions, or previous studies.

6. Focus groups: Researchers facilitate group discussions to collect data from multiple participants simultaneously.

7. Case studies: Researchers conduct an in-depth analysis of a single individual, group, or organization.

By using these methods, researchers collect data that can be analyzed using statistical techniques to draw meaningful insights and make informed conclusions.