Scientific Tables and Graphs

Good Scientific Tables and Their Graphs

• Scientific tables and graphs are essential tools for organizing, interpreting, and presenting data collected during investigations.

What is a Scientific Table?

• A scientific table organizes collected data and observations made during an investigation.
• Tables make it easier to read information, find patterns in the results, and aid analysis.

Features of a Good Scientific Table

• The independent variable (IV) systematically occupies the first column, followed by the dependent variable (DV) column(s).
• Each column should be clearly labeled with the type of variable observed.
• Units for each variable are included with labels and are NOT repeated throughout the table.
• The table should be provided with a number and descriptive title.
• Tables should have ruled borders for clarity and organization.
• Tables may include numerous trials and the average of the trials.

Graphing Tabulated Data

• Graphs simplify interpreting information, identifying trends, and drawing conclusions from data.
• The type of graph to use is determined by the data you have.

Types of Data

• Categorical data are non-numerical or qualitative, and contain Nominal and Ordinal types.
• The Nominal type refers to named categories like brands and colors.
• The Ordinal type refers to categories with an implied order, such as star ratings or rankings (e.g., 1st, 2nd, 3rd).
• Numerical data are quantitative and related to numbers.
• Numerical data is categorized as Discrete or Continuous.
• Discrete is data counted using whole counting numbers (1, 2, 3, 4, etc.)
• Continuous is data collected on a measuring scale.

Tables and Graphs

• Tables with numerical continuous data can be displayed on pH and growth scales, and can take on decimal values.
• Data with both IV and DV is displayed as ungrouped continuous numerical data using line graphs.
• Both vertical and horizontal gridlines are displayed on line graphs.
• Data with a categorical IV and continuous DV is shown as a column graph.
• Column graphs require only horizontal gridlines.

Categorical Data

• A nominal data set's categorical data is displayed when using a column graph.
• An ordinal data set's categorical data is displayed when using a column graph.

Graph Variables

• Histograms use gaps.
• Column graphs separate the different data categories.
• The dependent variable goes on the y-axis.
• The IV always goes on the x-axis.

Bar Graph and Histogram

• Histograms are used when the independent variable (IV) is numerical, continuous, and can be grouped.
• Data examples for a histogram would be groups like 0-3, 4-7, 8-11, etc.
• Column graphs are used when the independent variable (IV) data is categorical.

Important Notes About Histograms

• Data height of cherry trees must be numerical
• Gaps between data of 5 feet are used to measure
• Both vertical and horizontal gridlines are required, whereas column graphs only have horizontal gridlines.

Pie Charts

• Pie charts are used when the independent variable (IV) is categorical and the dependent variable (DV) is numerical (a fraction/portion of the whole).
• Pie charts show the fraction of the total.

Graph Selection

• Choose a line graph when data is numerical and both data sets are measurements.
• Choose Histograms when data is grouped and placed in intervals.
• Choose pie charts when data is categorical and numerical, and when the data expressed as parts of a total.
• Choose column graphs when each catergory has its own measurement.

Line Graphs

• Line graphs show how changes in the independent variable affect the dependent variable.

Simple Line Graphs

• Joins all the data points.

Scatterplot and Lines of Best Fit

• Scatterplots are used in science, especially in chemistry and physics experiments, to look for strong relationships between independent (IV) and dependent (DV) variables.
• Line in scatterplot can be smooth, straight or curved, and depends on where most of the data points sit.

Scatterplots Considerations

• Scatterplots ideas can be curved or straight, and passes through some points.
• No data points should be too far away from the line of best fit.
• There is an equal number of data points above and below the line.

Describing Relationships

• Graph A shows that acceleration changes as the force changes.
• Graph B shows an investigation involving a change in the mass.

Describing Best Fit Curved Lines

• This data displays a non-linear curve, displaying an increasing rate at which the curve rises.
• Another non-linear curve displays a decreasing rate.
• Concave up means it is increasing.
• Concave down means it is decreasing.

Describing Straight Lines

• Rising lines have a positive slope.
• Falling lines have a negative slope.
• Horizontal lines have a zero slope.
• Vertical lines have an undefined slope.
• The falling linear graph(negative slope).

Lines and Estimation

• Estimating values from an existing data set is known as interpolation when dealing with a line of best fit.
• Prediction by extending the line of best fit the value for a data point that is beyond the range of measurements is called extrapolation.
• The line of best fit is extended following the same trend.

Accuracy

• The outlier mark is an inaccurate data point.
• The inaccurate data point was caused by a mistake or human error when the data was collected.
• Do not include in a line of best fit.