Basic Course in StatisticsLaajuus (3 ECTS)

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 of his or her own field.

Content

1. The concept and the basic laws of probability, and random variables and their most common distributions.

2. Measurement uncertainty and propagation of errors.

3. Visualization of statistical data and basic statistics.

4. Confidence intervals and statistical tests, and their applications in statistical inference.

5. Regression analysis and applications in the student’s own filed of specialization.

6. Use of Excel or some other software in statistical analyses.

Qualifications

Basics in Engineering Mathematics, Equations and Matrices, Functions and Derivatives, Differential and Integral Calculus

Assessment criteria, satisfactory (1)

1. The student can calculate probabilities in elementary applications, and 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. The student is able to apply the laws of propagation of errors to elementary applications related to replicate measurements.

3. The student is able to make a histogram and calculate basic statistics of given data using some statistical software.

4. The student is able to calculate confidence limits for expected values and for standard deviations, and is able to make conclusions in statistical tests based on the p-value of the test.

5. The student is able to use linear regression analysis in elementary calibration problems.

6. The student takes part into the computer labs and carries out the given exercises acceptably.

Assessment criteria, good (3)

1. The student is able to use the laws of probability in statistical inference, and he or she is able to find an appropriate distribution in typical applications.

2. The student can approximate the standard measurement uncertainty of nonlinear expressions.

3. The student is able to draw conclusions based on graphs and statistics of given data.

4. The student is able to apply confidence intervals in statistical inference, and he or she is able to formulate statistical hypotheses into a given problem.

5. The student is able to interpret basic regression statistics.

Assessment criteria, excellent (5)

1. The student is able to apply his/her knowledge about statistical distributions and Monte Carlo simulation to statistical tests or measurement uncertainty estimation.

2. The student is able to describe the nature of given statistical data using several different visualization and computational tools.

3. Using literature and other available information, the student is able to choose and use statistical tests in new applications.

4. The student is able to transform typical expressions of his or her field of specialization into the linear regression form.