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BSTATS QUIZ 1
chapters 1.1,1.2,1.3,2.1,2.2,2.3,2.4,2.6,2.7,3.1,3.2,3.3, and 3.4
| Term | Definition |
|---|---|
| Statistics | The mathematical theory of analyzing data |
| Probability | Deals with the chance of an event occurring |
| Population | All individuals or items of interest in a study |
| Sample | A subset of the population from which the data was collected |
| Parameter | A numerical characteristic of a population |
| Statistic | A numerical characteristic of a sample |
| Variable | A characteristic of interest for each person or object in a population |
| Data | Individual items of information that come from a population or sample |
| Data | Can come from a population or a sample and can be defined as: qualitative (categorical), quantitative discrete, or quantitative continuous |
| Qualitative (categorical) | Data that consists of names or labels. Example: colors of backpacks |
| Quantitative discrete | Numerical data that can be counted. Example: Number of books |
| Quantitative continuous | Numerical data that can take any value within a range. Example: Distances from homes to college |
| Simple random sampling | Each member of the population has an equal chance of getting selected |
| Stratified sampling | The population is divided into groups, and a random sample is taken from each group |
| Systematic sampling | Selecting every nth number from a population |
| Cluster sampling | Dividing the population into groups and then randomly selecting whole groups |
| Convenience sampling | Selecting a sample that is readily available, which may result in bias |
| Variation in data | Data from a sample that will vary from the population and between samples. A sample size is based on desired precision and not a function of population size. |
| Stem and leaf plot | Shows all data values within a class |
| Line graph | Useful for finding trends over time |
| Histogram | Displays large data sets using contiguous boxes. Shows the shape, center, and spread of the data |
| Frequency table | Used to organize data, showing how many times a value appears |
| Relative frequency | Shows the proportion of data points for each value |
| Cumulative relative frequency | Shows the accumulation of relative frequencies |
| Percentiles | Divide the data into 100 equal parts. The nth percentile is the value below which n% of the data falls |
| Quartiles | Divide the data into 4 equal parts |
| Q1 | 25th percentile |
| Q2 | 50th percentile, aka the median |
| Q3 | 75th percentile |
| Interquartile range | Measures the spread of the middle 50% of the data, calculated as Q3-Q1 |
| Mean | Average of the data, calculated by adding all of the values and dividing by the number of values |
| Mode | The value that occurs most frequently |
| Skewness | Measures the asymmetry of a distribution |
| spread | Measures the variability of data |
| Sample standard deviation | Measures the spread of data around the sample mean. The denominator is n-1, where n is the sample size |
| population standard deviation | Measures the spread of data around the population mean. The denominator is N, the population size |
| Coefficient of variation | A measure of relative variability |
| Probability | Measures how certain we are of the outcomes of an experiment or activity |
| Chance experiment | Has a result that is not yet predetermined |
| Event | A subset of outcomes from an experiment |
| Sample Space | The set of all possible outcomes of an experiment |
| Independent events | The outcome of one event does not affect the outcome of another event |
| Mutually exclusive events | Events that cannot occur at the same time |
| Multiplication rule | Used to determine the probability of two independent events happening. P (A and B_ = P(A) + P(B) if A and B are independent |
| Addition rule | Used to determine the probability of either one or the other of two events happening. P(A or B) = P(A) + P(B) - P(A and B) |
| Compliment rule | P(A') = 1- P(A) |
| Contingency tables | Display data to calculate probabilities, especially conditional probabilities, involving two variables |
| Probability trees | Use branches to show the different outcomes of an experiment, making it easier to visualize complex probability questions |
| sum | =SUM(range) |
| average | =AVERAGE(range) |
| count | =COUNT(range) |
| average with criteria | =AVERAGEIF (range, criteria range, criteria) |
Created by:
isabella.ellison
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