Analysis of Experimental DataLaajuus (4 cr)

Objective

The student
• understands the importance of measurement uncertainty associated with all measurement data and can take it into account when making decisions
• can visualise and interpret statistical data
• is familiar with confidence intervals, statistical tests and regression analysis and can apply them to simple problem-solving situations in the interpretation of research results in their field.

Content

• Random variables and their most common distributions
• Visualisation of statistical data and basic statistics
• Confidence intervals and statistical tests, and their applications in statistical inference
• Variance and regression analysis and applications in student’s own field of specialisation
• Use of Excel or some other software in statistical analyses

Qualifications

Mathematics and Physics in Chemical Analysis 5 ECTS

Assessment criteria, satisfactory (1)

The student
• can name the most common distributions and calculate the associated probabilities and estimate the probabilities associated with a normal distribution
• can draw a histogram from given data and calculate the most common indicators using statistical software
• is able to calculate confidence intervals for the expected value and standard deviation and to carry out simple statistical tests and solve test conclusions on the basis of critical values and p-value
• can apply regression analysis in the most common linear calibration situations.

Assessment criteria, good (3)

The student
• can draw conclusions based on statistical indicators and graphical representations
• can apply confidence intervals in statistical decision making and formulate test hypotheses appropriate to a given benchmarking problem
• is able to interpret the key variables in analysis of variance and regression.

Assessment criteria, excellent (5)

The student
• can assess the nature of statistical data using a variety of graphical representations and indicators
• can apply tests to new situations using literature or other available information
• can use analysis of variance and regression to solve the most common problems in their field.

Assessment criteria, approved/failed

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