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TOPIC 1: RANDOM VARIABLES & PROBABILITY DISTRIBUTIONS
Q1: What is a quantitative value that represents the outcomes from an experiment?
Answer: Random Variable
Q2: What are the 2 kinds of random variables?
Answer: Discrete (countable) and Continuous (decimals)
Q3: What is the most common type of continuous probability distribution?
Answer: Normal distribution
Q4: What are some other names for a continuous probability distribution?
Answer: Probability curve and probability density function (pdf)
Q5: What is the total area under the curve if f(x) always equal to?
Answer: 1 or 100%
Q6: What is an area under a continuous probability distribution?
Answer: A probability
Q7: How many types of normal curves are there?
Answer: An infinite amount
Q8: What does the shape of any individual normal curve depend on?
Answer: Its specific mean and standard deviation (also median and mode)
Q9: What is the highest point over?
Answer: The mean, median, mode
Q10: Is the normal curve symmetric?
Answer: Yes (left and right are mirror images)
Q11: What does a larger standard deviation do to a curve?
Answer: Makes it shorter and wider
Q12: Do the tails of a normal curve ever touch the horizontal axis?
Answer: No
Q13: The specific shape of each normal distribution is determined by its ________ and ________.
Answer: mean, standard deviation
Q14: A continuous probability distribution having a rectangular shape, where the probability is evenly
distributed over an interval of numbers is a(n) ________ distribution.
Answer: uniform
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,Q15: The area under the curve of a valid continuous probability distribution must ________.
Answer: equal 1
Q16: A standard normal distribution has a mean of ________ and standard deviation of ________.
Answer: zero, one
Q17: The mean of a standard normal distribution is always equal to ________.
Answer: 0
Q18: The ________ is a graphic that is used to visually check whether data come from a normal population.
Answer: normal probability plot
Q19: It is appropriate to use the uniform distribution to describe a continuous random variable x when
relative frequencies of all possible values of x are about the ________.
Answer: same
Q20: The normal approximation of the binomial distribution is appropriate when ________.
Answer: np ≥ 5 & n(1 − p) ≥ 5
TOPIC 2: THE NORMAL DISTRIBUTION & Z-SCORES
Q21: The z value tells us the number of ________ that a value of x is from the mean.
Answer: standard deviations
Q22: A positive z-score indicates an ________.
Answer: outlier > 3 is unusual
Q23: A negative z-score indicates an ________.
Answer: outlier < -3 is unusual
Q24: The grade a student received on an examination was transformed to a z value, which was negative.
Therefore, we know that he scored ________.
Answer: below the mean
Q25: The fill weight of a certain brand of adult cereal is normally distributed with a mean of 910 grams and a
standard deviation of 5 grams. We calculated the value of z for a specific box of this brand of cereal, and the z
value was negative. This negative z value indicates that the fill weight is ________.
Answer: less than 910 grams
Q26: Which of the following statements is NOT a property of the normal probability distribution?
Answer: 95.44 percent of all possible observed values of the random variable x are within plus or minus three
standard deviations of the population mean
Q27: If the random variable x is normally distributed, ______ percent of all possible observed values of x will
be within three standard deviations of the mean.
Answer: 99.73
Q28: ________ values of the standard deviation result in a normal curve that is wider and flatter.
Answer: Larger
Q29: What percent of the area under the normal curve is within 1 standard deviation to the left and right?
Answer: 68%
Q30: What percent of the area under the normal curve is within 2 standard deviations to the left and right?
Answer: 95%
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, Q31: What percent of the area under the normal curve is within 3 standard deviations to the left and right?
Answer: 99.7%
TOPIC 3: SAMPLING & POINT ESTIMATION
Q32: What is x̄?
Answer: The sample mean
Q33: What is n?
Answer: Sample size
Q34: What is N?
Answer: Population size
Q35: Is calculating population mean easy to do?
Answer: Usually no, which is why we take samples
Q36: Why do we take samples?
Answer: The value of x̄ (sample mean) is used to make inferences about the value of μ (population mean)
Q37: What is a statistical inference?
Answer: Point estimation
Q38: What is the point estimation sample mean?
Answer: x̄ (x-bar)
Q39: What is the point estimation for sample standard deviation?
Answer: S
Q40: What is the point estimation for sample proportion?
Answer: p̂ (p-hat)
Q41: What is the point estimation for population mean (μ)?
Answer: x̄ (x-bar)
Q42: Standard deviation of the sample = ________.
Answer: σ / √n
TOPIC 4: SAMPLE PROPORTION & CONFIDENCE INTERVALS
Q43: What is sample proportion (p̂)?
Answer: Sample of the population, p̂ (p-hat), that we use because we do not know the parameter of the whole
population, p. p = p̂ most of the time but not always
Q44: What is standard deviation (in the context of sample proportion)?
Answer: The typical difference between p and p̂. The proportion from sample, p̂, is not equal to p. Typically the
estimate p̂ will be off by √(pq/n)
Q45: What is a confidence interval?
Answer: Assume symmetry, p̂ ± 2 × SD(p̂) for 95% confidence interval, so 95/100 will contain p
Q46: What are the confidence intervals for proportions?
Answer:
• 68%: (p − √(pq/n), p + √(pq/n))
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