A previous study found that of people preferred drinking Pepsi over Coca Cola. Use a normal distribution to approximate the probability that a random sample of people reveals people or more preferring Pepsi.
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically1h 48m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables2h 55m
- 6. Normal Distribution & Continuous Random Variables1h 48m
- 7. Sampling Distributions & Confidence Intervals: Mean2h 8m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 20m
- 9. Hypothesis Testing for One Sample2h 23m
- 10. Hypothesis Testing for Two Samples3h 25m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 30m
- 14. ANOVA1h 4m
8. Sampling Distributions & Confidence Intervals: Proportion
Sampling Distribution of Sample Proportion
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A bank analyzes customer adoption of its new mobile banking app. Historically, 45% of customers use online banking services. Use a normal distribution to approximate the probability that between 62 and 70 customers out of a sample of 100 will adopt the online banking service.
A
0.00165
B
0.000463
C
0.99
D
0.01

1
Identify the problem as a binomial distribution problem where n = 100 (sample size) and p = 0.45 (probability of success).
Use the normal approximation to the binomial distribution. Calculate the mean (μ) and standard deviation (σ) of the binomial distribution using the formulas: μ = n * p and σ = sqrt(n * p * (1 - p)).
Convert the binomial problem to a normal distribution problem by applying the continuity correction. For the range 62 to 70, adjust the values to 61.5 and 70.5.
Calculate the z-scores for 61.5 and 70.5 using the formula: z = (X - μ) / σ, where X is the value for which you are calculating the z-score.
Use the standard normal distribution table to find the probabilities corresponding to the calculated z-scores and determine the probability that the number of customers is between 62 and 70 by finding the difference between these probabilities.
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