Study

2-Var Stats

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  • Interpret the value r^2 = 0.646 for this model.
    64.6% of the variability in the percent of the grass area burned is accounted for by the least-squares regression line with x = wildebeest abundance.
  • Calculate and interpret the residual for the tortoise with carapace length 298 millimeters.
    2.6
  • Estimate r
    close to -1
  • Would you be willing to use the regression line to predict the long-jump distance for a student whose 40-yard sprint time is 3 seconds? Explain.
    No, far outside data value
  • Find the equation of the least-squares regression line for predicting the number of wins from number of goals scored.
    Y=−0.15+0.29x
  • Interpret r=.45
    somewhat weak and positive
  • Calculate a quadratic model for these data using carapace length as the explanatory variable
    Y =−0.0106x^2 +6.6181x−1018.9553
  • make a segmented bar chart
    expl = age
  • Calculate Correlation
    .89
  • Use it to determine whether the regression model is appropriate.
    Yes
  • Use technology to calculate the equation of the least-squares regression line relating y = number of larvae to x = number of stumps.
    y = −1.29 + 11.89x
  • Interpret the value s = 15.99 for this model.
    The actual percent of the grass area burned is typically about 15.99% away from its predicted percent of the grass area burned using the least-squares regressio
  • Predict the interval of time between eruptions if the previous eruption lasted 4 minutes
    86.51 minutes
  • Use it to determine whether the regression model is appropriate.
    yes
  • Predict the long-jump distance for a student who had a 40-yard-dash time of 6 seconds
    140.8 inches
  • Estimate r
    Close to 1
  • Calculate and interpret the residual for March, when the average temperature was 49.4°F and Joan used an average of 520 cubic feet per day.
    443.422 cubicfeetperday, res=76.578
  • Use technology to calculate the equation of the least-squares regression line relating y = price to x = screen size.
    Y = −575.23 + 25.41x
  • Interpret the slope of the regression line.
    decreases by 19.87 cubic feet per day for each additional degree of Fahrenheit for the average monthly temperature
  • Use it to determine whether the regression model is appropriate.
    No
  • Calculate the correlation
    .84
  • Find the Residual.
    2.07 minutes
  • Make a scatterplot
    2.2 #5