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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Descriptive Statistics | 25% | - Types of data: categorical, discrete, continuous - Measures of spread: range, IQR, variance, standard deviation - Graphical displays: histograms, boxplots, scatterplots - Measures of center: mean, median, mode |
| Topic 2: Basic Numeracy & Algebra | 15% | - Exponents, roots, and basic formulas - Linear equations, inequalities, graphing functions - Arithmetic operations, fractions, decimals, percentages |
| Topic 3: Inferential Statistics & Study Design | 20% | - Observational studies vs experiments - Hypothesis testing framework and interpretation - Sampling methods and bias - Confidence intervals for means/proportions |
| Topic 4: Correlation & Regression | 20% | - Simple linear regression models - Correlation coefficient and interpretation - Predictions and limitations of regression - Interpreting slope, intercept, and R-squared |
| Topic 5: Probability Concepts | 20% | - Conditional probability and Venn diagrams - Probability rules, independent and dependent events - Normal distribution and empirical rule - Discrete and continuous probability distributions |
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145. Frage
Probability of rolling sum = 12 = ?
Antwort: C
Begründung:
Rolling two six-sided dice produces 36 equally likely ordered outcomes. A sum of 12 can occur only when both dice show 6, giving the single ordered pair (6, 6). Since there is exactly 1 favorable outcome out of 36 total outcomes, the probability is 1/36. This is structurally similar to rolling a sum of 2, where only (1, 1) works. Option B, 1/6, is much too large and would apply to one specified face on one die. Option C, 2/36, would require two different ordered outcomes, but no pair other than (6, 6) sums to 12. Option D, 1/12, also overstates the probability. Extreme sums such as 2 and 12 are least likely because they have only one possible ordered combination. Study Guide references/topics: sample spaces, dice sums, theoretical probability, equally likely outcomes.
146. Frage
Probability of rolling an odd number on a die:
Antwort: D
Begründung:
A standard six-sided die has six equally likely outcomes: 1, 2, 3, 4, 5, and 6. The odd outcomes are 1, 3, and
5. Thus, there are 3 favorable outcomes out of 6 possible outcomes. The probability is 3/6, which simplifies to
1/2. This means an odd number is just as likely as an even number on a fair die. Option B, 1/3, would represent 2 favorable outcomes out of 6, which is not correct. Option C, 1/6, is the probability of rolling one specific number, such as only a 1. Option D, 2/3, would require 4 favorable outcomes out of 6. Since exactly half the faces are odd, the probability is one-half. Study Guide references/topics: theoretical probability, equally likely outcomes, sample space, favorable outcomes.
147. Frage
Review the following inequality:
y # #4x + 1
Which shaded region is described by this inequality?
Antwort: B
Begründung:
The inequality y # #4x + 1 has boundary line y = #4x + 1. The slope is #4, so the line must decrease steeply from left to right. The y-intercept is 1, so the line must cross the vertical axis at y = 1. Because the inequality uses "#," the boundary line must be solid, meaning points on the line are included in the solution set. The solution region must be below the line because y is less than or equal to the expression #4x + 1. A quick test point confirms this. Substitute (0, 0): 0 # #4(0) + 1, giving 0 # 1, which is true. Therefore, the shaded solution region must include the origin. Graph D shows a solid, steep downward-sloping line crossing the y-axis near 1 and shades the region containing the origin and below the boundary. References/topics from the Study Guide:
linear inequalities, slope-intercept form, boundary lines, test-point method.
148. Frage
Which distribution models number of successes in fixed independent trials?
Antwort: A
Begründung:
The binomial distribution models the number of successes in a fixed number of independent trials when each trial has only two possible outcomes, usually labeled success and failure, and the probability of success remains constant from trial to trial. These four conditions define the binomial setting: fixed number of trials, independent trials, two outcomes per trial, and constant success probability. Examples include the number of heads in 10 coin flips, the number of defective items in a sample when the defect probability is constant, or the number of students who pass an exam out of a fixed group. The normal distribution describes continuous bell-shaped data, not counts of successes. The Poisson distribution models counts of events occurring over a fixed interval when events occur at a constant average rate. The uniform distribution assigns equal probability across outcomes or intervals. Because the question explicitly states "number of successes" and "fixed independent trials," the correct model is binomial. Study Guide references/topics: binomial distribution, independent trials, success probability, discrete random variables.
149. Frage
Poisson mean = 4. Probability of exactly 2 events?