Somewhere in the Middle
In this activity, students will explore the Mean Value Theorem. Students will find out when the tangent line is parallel to the secant line passing through the endpoints of an interval to help them find the values of c guaranteed to exist by the MVT. Students will also test functions where the hy...https://education.ti.com/en/activity/detail/somewhere-in-the-middle_1
It's To Be Expected
Students use a tree diagram to find theoretical probabilities and use this information in a spreadsheet to find the expected value.https://education.ti.com/en/activity/detail/its-to-be-expected_1
Resampling
This lesson involves approximate sampling distributions obtained from simulations based directly on a single sample. The focus of the lesson is on conducting hypothesis tests in situations for which the conditions of more traditional methods are not met.https://education.ti.com/en/activity/detail/resampling
Trend or Noise?
This lesson involves investigating aspects of statistical information reported in the media or other venues, aspects that are often misunderstood by those unfamiliar with sampling.https://education.ti.com/en/activity/detail/trend-or-noise
Transforming Univariate Data
This lesson involves square root, logarithmic, square, and exponentiation transformations of skewed univariate data using a given data set.https://education.ti.com/en/activity/detail/transforming-univariate-data
How Many?
Students will explore Bernoulli probabilities. They will use them to calculate the probabilities of various single and cumulative events. They will also explore the Bernoulli probability distribution.https://education.ti.com/en/activity/detail/how-many
Transforming Bivariate Data
This lesson involves square root, semi-log, and log-log transformations of curved bivariate data using given data sets.https://education.ti.com/en/activity/detail/transforming-bivariate-data
Tossing Dice
This lesson involves simulating tossing two fair dice, recording the sum of the faces, and creating a dotplot of the sums.https://education.ti.com/en/activity/detail/tossing-dice
Why t?
This lesson involves examining the variability of individual elements and their related standardized test statistics when those elements are drawn randomly from a given normally-distributed population.https://education.ti.com/en/activity/detail/why-t
Tootsie Pops & Hand Span
Students will collect data, find the linear regression model of the data, and address aspects of the data that affect regression.https://education.ti.com/en/activity/detail/tootsie-pops--hand-span
Why np Min?
This lesson involves examining the general shape of binomial distributions for a variety of values of n and p.https://education.ti.com/en/activity/detail/why-np-min
Why Divide by n-1?
Students will investigate calculating a sample variance using both n and n-1 as the divisor for samples drawn with and without replacement.https://education.ti.com/en/activity/detail/why-divide-by-n1
What’s Normal, Anyway?
In this activity, students explore the normal distribution and several of its most interesting properties. First, they use a histogram of data from a binomial experiment to examine the general shape of a normal curve. Then, they use a dynamic illustration to make observations, using sliders to ch...https://education.ti.com/en/activity/detail/whats-normal-anyway
What’s My Model?
Students will investigate several different regression models and determine which of the models makes the most sense, based upon a real-world situation (cooling a cup of hot chocolate).https://education.ti.com/en/activity/detail/whats-my-model
Type 2 Error
This activity allows students to experiment with different alpha levels and alternative hypotheses to investigate the relationship among types of error and power.https://education.ti.com/en/activity/detail/type-2-error
Population Mean: σ unknown
Students calculate confidence intervals to estimate the true population mean when the standard deviation of the population is not known.https://education.ti.com/en/activity/detail/population-mean-σ-unknown
Normal Probability Plot
This lesson involves creating a normal probability plot for several data sets involving height to examine the appearance of such plots when the distribution is approximately normal.https://education.ti.com/en/activity/detail/normal-probability-plot
NASA - Spacewalk Training
In this activity, students will plot data, looks at patterns, and draw conclusions given a real-world context of astronauts training in the Neutral Buoyancy Laboratory (NBL) in Houston, TX.https://education.ti.com/en/activity/detail/nasa--spacewalk-training
Multiple Boxplots
This lesson involves analyzing three parallel boxplots.https://education.ti.com/en/activity/detail/multiple-boxplots
Means With Confidence
Students estimate the true mean of a population when the standard deviation is known by finding the sample mean, margin of error and confidence interval.https://education.ti.com/en/activity/detail/means-with-confidence_1
Re-Expressing Data
The students will learn to re-express data as a linear relationship even though the raw data does not fit a linear model. Students will learn important concepts involving data transformation and re-expression.https://education.ti.com/en/activity/detail/reexpressing-data
Computing with Mathematical Formulas
Evaluate formulas for given values of a variable.https://education.ti.com/en/activity/detail/computing-with-mathematical-formulas
Catching the Rays
Students will fit a sinusoidal function to a set of data. The data are the number of hours of daylight starting January 1st and collected on the first and sixteenth days of the months in Thunder Bay, Ontario, Canada.https://education.ti.com/en/activity/detail/catching-the-rays
Cell Phone Range
Students will learn to identify the domain and range of various real-world step functions. They will graphically explore numerical data points and observe step functions. Open and closed points on a graph are investigated and discussed.https://education.ti.com/en/activity/detail/cell-phone-range_1