Data Management & Statistics PDF

# Data Management ## Statistics - Collection - Organization - Analysis - Presentation - Interpretation Statistics deals with the collection, presentation, organization, analysis, and interpretation of data. ## Types of Statistics ### Descriptive Statistics - Summarizes and describes the main...

# Data Management ## Statistics - Collection - Organization - Analysis - Presentation - Interpretation Statistics deals with the collection, presentation, organization, analysis, and interpretation of data. ## Types of Statistics ### Descriptive Statistics - Summarizes and describes the main features of a dataset. - Helps understand data at a glance by showing things like: - How big or small the numbers are (e.g., average height) - How spread out the data is (e.g., income range) - What patterns or trends exist (e.g., most common age group) - Uses numbers, charts, and graphs to give a snapshot of the data without making predictions or conclusions beyond what the data shows. ### Inferential Statistics - Makes predictions or generalizations from a sample of data to a larger population. - Tries to answer questions and make conclusions beyond the data you have. ## Important concepts ### It helps you figure out things like: - What is the average height of all students in the school? - Will this new teaching method improve test scores? - What is the probability that a customer will buy this product? ### Sample - A subset of the population. ### Population - The collection of all elements which you are interested to study. ### Variable - The characteristic or attribute or the information you are interested to get from your respondents or subjects or the elements (broad). ### Variable of Interest - The variable written specified completely. - Just the variable itself but in a complete thought. - For example: Height of a male IT student, Monthly income in pesos. ### Parameter - Describes a **population**, which is the entire group you're studying. - For example: The average height of all students in a school is a parameter. ### Statistic - Describes a **sample**, which is a smaller group taken from the population. - For example: The average height of 100 students surveyed is a statistic. ### Types of Statistics: #### Applied Statistics - Concerned with the procedures and techniques used in the collection, presentation, organization, analysis, and interpretation of data. #### Theoretical Statistics - Concerned with the development of the mathematical foundations of the methods used in applied statistics. ### Independent Variable - The variable that you control or change to see how it affects something else. ### Dependent Variable - The variable that you measure to see how it is affected by changes in the independent variable. ## Use of Documented Data ### Primary Data - Documented by the primary source. The data collectors themselves documented this data. ### Secondary Data - Documented by the secondary source: an individual/agency, other than the data collectors, documented this data. ## Methods of Data Collection ### Surveys - Personal Interview - Telephone Interview - Use of Questionnaire - Focus Group Discussion ### Experiment - There is direct human intervention on the conditions that may affect the values of the variable of interest. ### Observation Method - Method of collecting data on the phenomenon of interest by recording the observations made about the phenomenon as it actually happens. ## Level of Measurement - **Ratio**: 4 - **Interval**: 3 - **Ordinal**: 2 - **Nominal**: 1 **Ratio:** - Is it possible to have a zero? If yes, does that "zero" mean nothing, empty, no value?<br> - Mathematical operations are meaningful. 1. The numbers in the system are used to classify a person/object into distinct, non-overlapping, and exhaustive categories. 2. The system arranges the categories according to magnitude. 3. The system has a fixed unit of measurement representing a set size throughout the scale. 4. The system has an absolute zero. ## Data Presentation - **Different ways to present the data:** 1. To see distribution. 2. To know the best representation. - **Textual format:** Describing the data. - **Tabular:** More organized than textual format. | Age Group | Count | Percentage | |---|---|---| | 12-18 | 95 | 45.24 (45%) | | 19 - 24 | 105 | 50% | | 25-30 | 1 | 0.5% | | **TOTAL** | **210**| **100%** | - **Graphical method**: Deals with geographical locations; helps to present to the audience. ## Measures of Central Tendency - Tend to be in the center (representative). - **Mean:** $\sum_{i=1}^{n} \frac{x_i}{n}$ - **Median:** Last - element / First-element - **Mode:** ## Quanti-Level, Ratio - **Variance:** mean, median, mode - **Standard Deviation:** - Median - Mode - Range = max-min - Coefficient of Variation (CV) = $\frac{standard\ deviation}{mean} \times 100$