Fundamentals of Mathematics and Data AnalyticsLaajuus (5 cr)
Code: 4A00HH72
Credits
5 op
Objectives
Mathematics
After completing the course, the student will master the most important calculation tasks in the ict field and business life. He/she knows how to convert numbers between the 2-, 10-, and 16-systems, apply bin-, dec- and hex-numbers to define networks, solve percentage calculations (e.g. taxation, margin yield), solve interest and compound interest calculations and convert sums of money from earlier and later with indexes.
Data Analytics
After completing the Data Analytics Basics module, the student will be able to effectively utilize spreadsheet software for data processing, analysis, and reporting. The student will master the basic functions of spreadsheet software, such as data entry, modification, and calculations, as well as advanced features, including formulas, functions, add-ons, statistical analysis a data visualization. They will be able to use the software for data collection, cleaning, and analysis, ensuring consistency across data sources and evaluating the reliability of results.
Additionally, the student will have the skills to apply data analytics to business development. The course provides excellent capabilities for the versatile and efficient use of spreadsheet software in data analytics.
Content
Mathematics
• Bin, dec and hex systems
• Number conversions
• IPv4 address and subnet mask
• IPv6 address
• Percentage calculation
• Calculation of interest
• Compound interest, taxes, and profitability
• Indices and applying them
Data Analytics
• Basics of data analytics
• Basic use of spreadsheet software
• Advanced use and functions of spreadsheet software
• Data visualization
• Statistical data analysis
Assessment criteria, satisfactory (1-2)
Mathematics: The student knows how to convert numbers between 2-, 10-, and 16-systems and construct an IPv4 and IPv6 network. He/she masters the basic level of calculating percentages, interests, taxes, profitability, indices.
Data Analytics: The student can enter and modify data in a spreadsheet program and use basic functions (e.g., addition, subtraction, calculating averages). Data preprocessing and visualization are limited to simple methods, and identifying sources of error or critically evaluating results is not yet systematic.
Assessment criteria, good (3-4)
Mathematics: The student manages well the 2-, 10-, and 16-number systems, and knows how to use them when defining and planning IPv4 and IPv6 networks. He/she typifies a good understanding of percentage calculation and knows how to apply it in business contexts. He/she is good with calculating percentages, interests, compound interests, taxes, profitability, and indices.
Data Analytics: The student is able to use more advanced features in a spreadsheet program, such as pivot tables and various functions, and can produce clear charts and reports. They recognize the need for data cleaning and can carry out basic statistical analysis. Assessing the reliability of data sources and identifying errors is done reasonably well.
Assessment criteria, excellent (5)
The student controls in depth the 2-, 10- and 16-number systems and knows how to use them in an advanced way in definition and planning Mathematics: IPv4 and IPv6 networks. He/she typifies deep understanding of percentage calculation and knows how to apply it in more complex situations. He/she understands deeply effects of taxation on business and can calculate taxes in more complex situations. He/she typifies strong competence in concepts of margin and profitability calculation and can apply them to realistic business situations. He/she typifies deep understanding of the use of indices and can them in a sophisticated way.
Data Analytics: The student demonstrates a diverse range of skills in using spreadsheet programs and extensively applies functions, add-ons, and statistical methods. They systematically plan and perform data processing, analysis, and visualization, and can clearly justify their choices. The student critically evaluates the reliability of the data.