a.
Import the data in JASP and run the logistic regression model on interest (provide a
full capture of the output).
b. Write the equation for the logistic regression based on the JASP output.
The JASP result can be used to derive the logistic regression model's equation.
It appears as follows: logit(p) = β0 + β1 * Temperature
Where: logit(p) is the log-odds of the probability of damage to the O-ring.
β 0 is the intercept coefficient.
β1 is the coefficient associated with the Temperature variable.
Therefore; β0= infinity (∞) β1=2.254x10-36
Temperature= 1.192×10-4
The Equation is P=∞+2.254x10-36 X 1.192×10-4 c.
c.Is the β estimate associated with Temperature statistically significant with a 5%
significance level? Interpret
The fact that the p-value is greater than 0.05 but less than 1 indicates that there isn't much
proof that the temperature variable affects the likelihood of O-ring degradation in a
meaningful way. We can see that the estimated odds ratios for the undamaged O-rings are less
than 1, which means that the likelihood of an undamaged O-ring is greater than the likelihood
of a damaged one for those O-rings in the first class.
d. Based on the output of the logistic model, is it justified that a part of the O-rings was
damaged because of temperature (Yes/No)? Interpret.
Based on the output of the logistic model, it does not determine to justify that part of the O
rings was damaged because of temperature. The corresponding Temperature variable value is
less than 1, it suggests that is no increase in temperature is associated with an increased odds
of O-ring damage.
Interpretation: Because the value is less than 1, it does not support any justification that
temperature is a contributing factor to much O-ring damage.
e. Find the model-estimated probability an O-ring being damaged for the following
ambient temperatures
Using the equation: log(p / (1 - p)) = β0 + β1 * Temperature
The Equation is P=∞+2.254x10-36 X 1.192×10-4 Log (1/(1-1))= ∞ + 2.254x10-36 x 51
=0.627x51= 31.97 = 0.627 x53= 33.231
=0.627 x55= 34.485 =0.627 x57= 35.739 log(p / (1 - p)) = β0 + β1 * Temperature
REFERENCE:
JASP Statistics. (2018, February 11). How to perform a logistic regression analysis in JASP
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