Data Analysis

Experimental Design

  • Repeated trials: scientists repeat trials to confirm findings (the more repeated trials, the better)

  • Means (means are the average of a data set; for example, in the set {1, 2, 4, 7}, the mean is 3.5 because 1+2+4+7=14/4 (# of elements) = 3.5

  • Variables

    • Independent Variable (IV)

      • Variable scientists change

      • For example, 0, 2, and 4 mL of water are example of levels of an IV

      • Often X-axis

    • Dependent Variable (DV)

      • Responds to the changes in the IV

      • Scientists measure this

      • Often Y-axis

  • Control

    • A control is a standard of comparison that researchers can use to compare levels of the Independent Variable to accurately make conclusions about the relationship between the IV and DV

  • Constants

    • Parts of the experiments that stay the same to prevent confounding variables (we want to measure the effect of the IV on the DV with on other variables involved that might skew the data)

All these components of Experimental Design are important so scientists can convey accurate and meaningful findings

Instruments to Gather Data

Scientists use various tools and equipment to gather data

Representing Data and Patterns in Data

Trends are patterns in data that researchers can use to predict or analyze data sets

To find the trend/pattern, look for the relationship between the IV and DV - as the IV increases, what happens to the DV?

In this graph:

  • Trend is that as temperature increases, the solubility decreases for all the compounds and elements

Bar graphs are used to represent different categories of IVs, line graphs show change over time, and pie charts show parts of wholes.

Sources of Experimental Error

  • All experiments are prone to experimental error because sometimes scientists can not measure data precisely enough

  • Errors are differences between observations and what occurs in nature (they are inaccuracies)

  • Types

    • Random error - due to chance

    • Systematic error - measurements that are consistently different

    • Instrumental error - instruments are inaccurate

    • Environmental error - factor in the environment, such as wind in the laboratory, leads to error

    • Human error is due to carelessness/limitations of human ability

  • Scientists try to reduce error by repeating trials

Once you're ready, try this quiz!

Check your answers!

Quiz Answers