A Lights-A-Lot quality inspector examines a sample of 25 strings of lights and finds that 6 are defective.
a. What is the experimental probability that a string of lights is defective?
b. What is the best prediction of the number of defective strings of lights in a delivery of 1,000 strings of lights?
3/500; 6 lights
6/25; 24 lights
1/40; 25 lights
6/25; 240 lights
I really need help. Fast.
To answer these questions, we will use the concept of experimental probability and apply it to the given information.
a. Experimental probability is the ratio of the number of favorable outcomes (in this case, defective strings of lights) to the total number of outcomes (the sample size of 25 strings of lights).
Step 1: Calculate the experimental probability.
Number of defective strings of lights = 6
Total number of strings of lights in the sample = 25
Experimental probability = Number of favorable outcomes / Total number of outcomes
Experimental probability = 6 / 25
Therefore, the experimental probability of a string of lights being defective is 6/25.
b. To predict the number of defective strings of lights in a delivery of 1,000 strings of lights, we can use the experimental probability found in part a and apply it to a larger sample size.
Step 2: Apply experimental probability to a larger sample size.
Number of strings of lights in the delivery = 1,000
Prediction of the number of defective strings of lights = Experimental probability * Total number of strings of lights in the delivery
Prediction of the number of defective strings of lights = (6/25) * 1,000
Therefore, the best prediction of the number of defective strings of lights in a delivery of 1,000 strings of lights is (6/25) * 1,000.