Download UNIT 4: INFERENCE Apply and extend previous understandings of

UNIT 4: INFERENCE
Apply and extend previous understandings of measurement and interpreting data.
MCC7.SP.1: Understand that statistics can be used to gain information about a population by examining a
sample of the population; generalizations about a population from a sample are valid only if the sample is
representative of that population. Understand that random sampling tends to produce representative
samples and support valid inferences.
MCC.SP.2: Use data from a random sample to draw inferences about a population with an unknown
characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the
variation in estimates or predictions. For example, estimate the mean word length in a book by randomly
sampling words from the book; predict the winner of a school election based on randomly sampled survey
data. Gauge how far off the estimate or prediction might be.
MCC7.SP.3. Informally assess the degree of visual overlap of two numerical data distributions with similar
variability, measuring the difference between the centers by expressing it as a multiple of a measure of
variability. For example, the mean height of players on the basketball team is 10 cm greater than the mean
height of players on the soccer team, about twice the variability (mean absolute deviation) on either team;
on a dot plot, the separation between the two distributions of heights is noticeable.
MCC7.SP.4. Use measures of center and measures of variability for numerical data from random samples to
draw informal comparative inferences about two populations. For example, decide whether the words in a
chapter of a seventh-grade science book are generally longer than the words in a chapter of a fourth-grade
science book.
 Skills for Review
o Collect/Analyze Data; Represent and interpret data; Types of Graphs
o Using data to draw inferences – sample populations; generalizations
o Measures of Center
o Measures of Variability - Box-and-Whisker Plots
Types of Graphs - Review
1. Bar graph – uses bars of different heights to compare categories of data
2. Double-bar graph – uses pairs of bars to compare categories of data
3. Line graph – uses points connected by line segments to show data; useful to show how data changes
over time, or when you want to find trends
4. Circle graph – divides a whole circle into sections; used to compare parts to parts, and to compare
parts to totals
5. Pictograph – uses pictures to compare categories of data
6. Line plot – uses X’s or other symbols to show information on a number line; useful and quick way to
display a set of data
7. frequency table – shows how the data can be grouped; Table – Intervals, Tally, Frequency
8. frequency distribution – organization of data; shows the number of pieces of data that fall into several
ranges of values (intervals of the same range)
9. frequency – the total number of pieces of data that fall into an interval
10. histogram – uses bars to show data from a frequency table; no gap between the bars in a histogram;
no gap between the intervals in a frequency table
The information you want to show determines the type of graph used to display data.
 Pictograph or bar graph – compare categories of data
 Histogram – compares categories of data that are grouped into intervals
 Line graph – shows changes over time or identifies trends
 Circle graph – compares part of a set of data to another part, or a part to a total; percentages
 Line plot – allows one to see data pictured over a number line; easy to see how often each data
item appears in a set
Vocabulary: frequency, grouped frequency table, maximum & minimum value, mean, median, mode, range,
measures of center, measures of spread, mutually exclusive, outlier, sample, simple random sampling,
population, biased sample, unbiased sample, mean absolute deviation(MAD), box-and-whisker plot(review)