Presentation, Interpretation, and Analysis of Data

• Attribute Data: countable or data that can be put into categories.
• Variable Data: measurement data, based on continuous scale.
• Bar Graphs. Bars of equal width representing different categories with the length of each bar corresponding to the value it represents.
• Histograms. Representing continuous data. The bars touch each other to show that the data is continuous. A rectangular figure with no spaces between them.
• Line graph. Data points are plotted on a graph, and lines are drawn to connect these points, showing trends or changes over time. Time series data, trend analysis, decrease or increase of data over time.
• Pie chart. Circle divided into slices. Part of a whole
• Scatter plots. Plotting individual data points on a graph with two axes to show relationships between variables. Correlation analysis, identify patterns, and outlier detection
• If the t-value (t-ratio) is bigger than the critical value, therefore you need to reject the null hypothesis.
• Data Collection. A process of collecting information regarding the variables that the researcher sought to examine, and to answer the objective/s of the research.
• Primary Data. First-hand information gathered from a specific purpose.
• Primary Data. Interview, Survey questionnaire, Direct Observation, Experiment
• Secondary Data. Second-hand information gathered from an existing collected data-primary data
• Secondary Data. DepED, PSA, NSO, World Bank, United Nation, NEDA
• Number the table, figure, or graph and provide a title.
• Table headings – keep it brief.
• Body – present information in its most meaningful and appropriate form
• Legend – place within the figure
• Caption – concise explanation.