Study Guide

Objective

The student realizes the importance of the measurement uncertainty, unavoidable in every measurement, and is able to take that into account in decision making. The student is able to visualize and interpret statistical data. The student knows confidence intervals, statistical tests, and regression analysis, and can apply them in solving typical simple applications in the laboratory field.

Content

1. Random variables and their most common distributions.
2. Visualization of statistical data and basic statistics.
3. Confidence intervals and statistical tests, and their applications in statistical inference.
4. Variance and regression analysis and applications in student’s own filed of specialization.
5. Use of Excel or some other software in statistical analyses.

Prerequisites

Mathematics and Physics in Chemical Analysis 5 op

Assessment criteria, satisfactory (1)

The student
1. can name some of the most common distributions and calculate probabilities related to them. The student can estimate probabilities related to the standard normal distribution.
2. is able to make a histogram and calculate basics statistics of given data using some statistical software.
3. is able to calculate confidence limits for expected values and for standard deviations, and is able to use statistical tests and make conclusions in statistical tests based on the p-value of the test and critical values.
4. is able use linear regression analysis in elementary calibration problems.

Assessment criteria, good (3)

The Student
1. is able to draw conclusions based on graphs and statistics of a given data.
2. is able to apply confidence intervals in statistical inference, and is able to formulate statistical hypotheses into a given problem.
3. is able to interpret basic analysis of variance and regression statistics.

Assessment criteria, excellent (5)

The Student
1. Using literature and other available information, the student is able to choose and use statistical tests in new applications.
2. is able to use analysis of variance or linear regression to solve most common problems in the laboratory field.