The numbers below show salmon population’s decrease since 1960. salmon = {{0, 10.02}, {5, 10.00}, {10, 7.61}, {15, 3.15}, {20, 4.59}, {25, 3.11}, {30, 2.22}}; TableForm[salmon, TableHeadings → {None, {"Years (after 1960)", "Salmon (mil)"}}] Years (after 1960) Salmon (mil) 0 10.02 5 10. 10 7.61 15 3.15 20 4.59 25 3.11 30 2.22 Pair like (10,7.61) shows there were 7.61 million salmon in 1970. Why 1970? Because t (the number in the left column) is number of years after 1960. A pair like (10, 7.61) is called a data-point. Because it shows some data (information), and geometrically it is a point (it has two numbers). A row in our table gives us a data-point. S1. Plot the data = create a scattergram. S2. Show the graph of a line that comes close to the points in your scattegram. The line might also be known as Best fit line, Regression Line, or Least-squares regression line. S3. Find the equation of a linear function connecting S, salmon population (in millions), with t, years since 1960. It is OK to use y for the function (S) and x for the variable (t). S4. What is the slope of the dependence? S5. What does the slope in this problem mean in simple, non-mathematical terms?
The numbers below show salmon population’s decrease since 1960. salmon = {{0, 10.02}, {5, 10.00}, {10, 7.61}, {15, 3.15}, {20, 4.59}, {25, 3.11}, {30, 2.22}}; TableForm[salmon, TableHeadings → {None, {"Years (after 1960)", "Salmon (mil)"}}] Years (after 1960) Salmon (mil) 0 10.02 5 10. 10 7.61 15 3.15 20 4.59 25 3.11 30 2.22 Pair like (10,7.61) shows there were 7.61 million salmon in 1970. Why 1970? Because t (the number in the left column) is number of years after 1960. A pair like (10, 7.61) is called a data-point. Because it shows some data (information), and geometrically it is a point (it has two numbers). A row in our table gives us a data-point. S1. Plot the data = create a scattergram.
S2. Show the graph of a line that comes close to the points in your scattegram.
The line might also be known as Best fit line, Regression Line, or Least-squares regression line.
S3. Find the equation of a linear
since 1960.
It is OK to use y for the function (S) and x for the variable (t).
S4. What is the slope of the dependence?
S5. What does the slope in this problem mean in simple, non-mathematical terms?
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