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The 3-hour, end-of-course exam is comprised of 46 questions, including 40 multiple-choice questions (50% of the exam) and 6 free-response questions (50% of the exam) .  \nThe exam covers the following course content categories:  \n• Exploring One-Variable Data: 15%‒23% of test questions  \n• Exploring Two-Variable Data: 5%‒7% of test questions  \n• Collecting Data: 12%‒15% of test questions  \n• Probability, Random Variables, and Probability Distributions: 10%‒20% of test questions  \n• Sampling Distributions: 7%‒12% of test questions  \n• Inference for Categorical Data: Proportions: 12%‒15% of test questions  \n• Inference for Quantitative Data: Means: 10%‒18% of test questions  \n• Inference for Categorical Data: Chi-Square: 2%‒5% of test questions  \n• Inference for Quantitative Data: Slopes: 2%‒5% of test questions  \nThis guide will offer an overview of the main tested subjects, along with sample AP multiplechoice questions that look like the questions you ’ll see on test day.  \nExploring One-Variable Data  \nOn your AP exam, 15‒23% of questions will fall under the topic of Exploring One-Variable Data.  \nVariables and Frequency Tables  \nA variable is a characteristic or quantity that potentially differs between individuals in a group. A categorical variable is one that that classifies an individual by group or category, while a quantitative variable takes on a numerical value that can be measured.  \n|  |  |  |\n| --- | --- | --- |\n|  | Examples of Variables\u003Cbr>|  |\n| Categorical variables The country in which a product is manufactured\u003Cbr>The political party with which a person is affiliated\u003Cbr>The color of a car Quantitative variables The height, in inches, of a person\u003Cbr>The number of red cars that pass through an intersection in a day\u003Cbr>It is important to recognize that it is possible for a categorical variable to look, superficially, like a number. For example, despite being composed of numbers, a zip code is categorical data. It does not represent any quantity or count; rather, it’s simply a label for a location.\u003Cbr>Quantitative variables can be further classified as discrete or continuous. A discrete variable can take on only countably many values. The number of possible values is either finite or countably infinite. In contrast, a continuous variable can take on uncountably many values. An important characteristic of a continuous variable is that between any two possible values another value can be found.\u003Cbr>Graphs for Categorical Variables\u003Cbr>A categorical variable can be represented in a frequency table, which shows how many individual items in a population fall into each category. For example, suppose a student was interested in which color of car is most popular. He collects data from the parking lot at school, and his results are shown in the following frequency table:\u003Cbr>Color Frequency Black 14 Red 6 Blue 5 Silver 11 White 6 Green 3 Yellow 1 Grey 4\u003Cbr>|  |  |\n\n\n| A relative frequency table gives the proportion of the total that is accounted for by each category. For example, in the previous data, 14 of the 50 cars, or 28%, were black. The full relative frequency table is as follows:\u003Cbr>Color Relative Frequency Black 28% Red 12% Blue 10% Silver 22% White 12% Green 6% Yellow 2% Grey 8%\u003Cbr>Note that the percentages add up to 100%, since all of the cars were of one of the colors represented in the table.\u003Cbr>A bar chart is a graph that represents the frequencies, or relative frequencies, of a categorical variable. The categories are organized along a horizontal axis, with a bar rising above each category. The height of the bar corresponds to the number of observations of that category. The vertical axis may be labeled with frequenci","cbCaioLzEivxijI8","https://ap.wps.com/l/cbCaioLzEivxijI8","pdf",2534567,76,"English","# Key Exam Details\n## Exploring One-Variable Data\n## Variables and Frequency Tables\n## Graphs for Categorical Variables\n## Graphs for Quantitative Variables","[{\"question\":\"What topics and percentages are tested in the AP Statistics exam?\",\"answer\":\"The exam covers Exploring One-Variable Data (15%–23%), Exploring Two-Variable Data (5%–7%), Collecting Data (12%–15%), and several inference and probability areas. The guide lists ranges for probability, sampling distributions, inference for categorical data (including proportions and chi-square), and inference for quantitative data (means and slopes).\"},{\"question\":\"How does the guide define categorical and quantitative variables?\",\"answer\":\"A variable is a characteristic or quantity that may differ between individuals. The guide defines categorical variables as grouping individuals by category, while quantitative variables take numerical values that can be measured, such as height or counts.\"},{\"question\":\"What is the difference between a bar chart and a histogram?\",\"answer\":\"The guide states that a bar chart represents the frequencies (or relative frequencies) of a categorical variable with bars for each category. A histogram is used for quantitative data, splitting the data into intervals (bins) and showing counts across those intervals.\"}]","AP Statistics - Study Guide | PDF",1789894218,192]