Should be done in TI-nspire

Should be done in TI-nspire

Should be done in TI-nspire
The purpose of this assignment is to investigate how an authentic data set can be described using a mathematical function. You have to play with different straight lines to “fit” the data as best as possible with a straight line. The goal is to gain an understanding of the method in linear regression.  You can choose to use the T-inspire file to work on. Delete the task text and instead write your own explanations of how to use the tools and what the task is about.  Task: “several over 100 years” The following dataset describes the development in the number of women in Denmark over the age of 100. year 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 No of women over 100 628 696 753 761 771 843 840 865 906 976 Denmark’s statistics a) The data set is entered in “lists and spreadsheets” on the next page and the application “diagrams and statistics” is opened next to it. Make a dot plot of the data set, where the number of women over 100 is on the y-axis and the number of years after 2008 is on the x-axis. Describe the trend in the development of the number of Danish women over 100 years of age. b) Then select “examine data” and “add movable line”. Drag the line until you think it “fits” the data points as best as possible. Write down the calculation formula for this “best straight line”. c) What criteria or considerations did you use when you had to place the best straight line, should it e.g. go through certain points? d) Select “examine data” again. Under “residuals” select “show residual squares”. Try again to pull the movable line until the sum of the squares becomes the smallest possible. Write down the new calculation rule for this “best straight line”. Is it different from the one you got before? e) You must now get nspire to determine the calculation rule for the line that fits the points best. For this, linear regression is used. You can do regression in “spreadsheets” or in “diagrams and statistics”. If you click residual squares” again, you can see what the program has found as the smallest sum. Compare the formula for your “best straight line” with the regression. Is there a difference? f) Is it possible that in Denmark in the year 2025 there will be more than 1200 women over 100 years of age?

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