Problem #2: The data show bug chirps per minute at different temperatures. The significant level is 0.05 Chirps in I min 900 500 902 600 700 1000 Temperature (°F) 77.3 80.3 73.9 78.9 67.1 88.7 a) What...


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Problem #2:<br>The data show bug chirps per minute at different temperatures. The significant level is 0.05<br>Chirps in I min<br>900<br>500<br>902<br>600<br>700<br>1000<br>Temperature (°F)<br>77.3<br>80.3<br>73.9<br>78.9<br>67.1<br>88.7<br>a) What is the regression equation?<br>b) Check the P-value. Is the P-value < a?<br>answer part c.<br>c) What is the best predicted temperature for a time when a bug is chirping at a rate of 1100 chirps per minute?<br>if yes use the line for prediction. If not, find the mean temperature to<br>StatCrunch commands: stat < regression < simple linear < choose x and y < choose Hypothesis test< Check if<br>P-value is less than or equal to a enter the value of X in the predicted value< compute!<br>If P-value is > a, the predicted value is the mean average of Y values.<br>© G. Nasnas<br>

Extracted text: Problem #2: The data show bug chirps per minute at different temperatures. The significant level is 0.05 Chirps in I min 900 500 902 600 700 1000 Temperature (°F) 77.3 80.3 73.9 78.9 67.1 88.7 a) What is the regression equation? b) Check the P-value. Is the P-value < a?="" answer="" part="" c.="" c)="" what="" is="" the="" best="" predicted="" temperature="" for="" a="" time="" when="" a="" bug="" is="" chirping="" at="" a="" rate="" of="" 1100="" chirps="" per="" minute?="" if="" yes="" use="" the="" line="" for="" prediction.="" if="" not,="" find="" the="" mean="" temperature="" to="" statcrunch="" commands:="" stat="">< regression="">< simple="" linear="">< choose="" x="" and="" y="">< choose="" hypothesis="">< check="" if="" p-value="" is="" less="" than="" or="" equal="" to="" a="" enter="" the="" value="" of="" x="" in="" the="" predicted="">< compute!="" if="" p-value="" is=""> a, the predicted value is the mean average of Y values. © G. Nasnas

Jun 02, 2022
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