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I am currently working on logistic regression in R and I have trained the model but when I am looking at summary of model, I am not able to understand what is z value and Pr(>|z|) explains ?

The z-value is the regression coefficient divided by standard error. If the z-value is too big in magnitude, it indicates that the corresponding true regression coefficient is not 0 and the corresponding X-variable matters. A good rule of thumb is to use a cut-off value of 2 which approximately corresponds to a two-sided hypothesis test with a significance level of \alpha=0.05.

In the output of the summary() function for the logistic regression model in R, the z value and Pr(>|z|) columns represent the statistical significance of each coefficient in the model.

The z value is the ratio of the estimated coefficient to its standard error. It measures the number of standard deviations that the estimated coefficient is away from zero. A higher absolute value of z value indicates that the estimated coefficient is more statistically significant.

The Pr(>|z|) column represents the p-value for each coefficient, which is the probability of observing a z value as extreme or more extreme than the observed value, assuming the null hypothesis that the coefficient is zero. A lower p-value indicates that the coefficient is more statistically significant, and a value less than 0.05 is often considered as evidence to reject the null hypothesis.

In the example provided, for the variable disp, the z value is -2.241, and the corresponding Pr(>|z|) is 0.025, which means that the coefficient for disp is statistically significant at the 5% significance level.