Please answer 1-11 I will attach the scatter diagram of the data for question #

Question

Please answer 1-11 I will attach the scatter diagram of the data for question # 3 but I need to have an answer if its a linear relationship? positive or negative? Linear Regression Assignment Answer the questions using the following scenario. Use excel whenever possible. Crickets make chirping noises by sliding their wings over each other. You notice that the number of chirps seems to increase when the temperature increases. You collect the following data of temperature (in degrees Fahrenheit) and the number of chirps per second for a striped ground cricket. Temperature Chirps per Second 88.6 93.3 80.6 69.7 69.4 79.6 80.6 76.3 71.6 84.3 75.2 82.0 83.3 82.6 83.5 20.0 19.8 17.1 14.7 15.4 15.0 16.0 14.4 16.0 18.4 15.5 17.1 16.2 17.2 17.0 1. What is the explanatory variable for the data? Why? 2. What is the response variable? Use excel to create a scatter diagram of the data. Print it out and attach it to your answers. Does there appear to be a linear relationship? It is positive or negative? 3.

Explanation / Answer

1)

Explanatory variable is temperature. It will determine how much the birds will chirp.

2)

Response variable is chirps per second. This is because it will be dependent on the temperature outside

4)

r=0.835

5)

Yes it does exist

6)

Slope is 0.2119

7)

Intercept is -0.3091

8)

Slope: For every increase of 1 in temperature, chirps would go up by 0.2119, keeping all other factors constant

Intercept: Chirps would remain constant at -0.3091 even when there is no temperature

9)

Number of chirps=-0.3091+0.2119*83.3

Number of chirps=17.34 (approx 18)

10)

19=-0.3091+0.2119x

91.12=x

11)

Yes we can

Number of chirps=-0.3091+0.2119*55

Number of chirps=11.3467 (approx 12)

SUMMARY OUTPUT Regression Statistics Multiple R 0.83514379 R Square 0.69746514 Adjusted R Square 0.67419323 Standard Error 0.97151773 Observations 15 ANOVA df SS MS F Significance F Regression 1 28.2873264 28.2873264 29.9702554 0.00010667 Residual 13 12.270007 0.94384669 Total 14 40.5573333 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -0.3091444 3.10858437 -0.0994486 0.9222993 -7.0248326 6.40654385 Temperature 0.21192501 0.03871123 5.4745096 0.00010667 0.12829448 0.29555554

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