Education Technology
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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

t Distributions

Students compare the t distribution to the standard normal distribution and use the invT command to find critical values for a t distribution.
https://education.ti.com/en/activity/detail/iti-distributions_1

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

Transforming Relationships

In this activity, students will assess the strength of a linear relationship using a residual plot. They will also calculate the correlation coefficient and coefficient of determination to assess the data set. Students will then learn to transform one or two variables in the relationship to creat...
https://education.ti.com/en/activity/detail/transforming-relationships_1

Family of t Curves

This lesson involves investigating how a t-distribution compares to a normal distribution.
https://education.ti.com/en/activity/detail/family-of-t-curves

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

Too Many Choices!

Students investigate the fundamental counting principle, permutations, and combinations.
https://education.ti.com/en/activity/detail/too-many-choices_1

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

Two-way Tables and Association

This lesson involves analyzing the results of a survey using a two-way frequency table.
https://education.ti.com/en/activity/detail/twoway-tables-and-association

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

Probability Simulations

Students use the random integer (randInt) command to simulate probability experiments. They also graph the number of trials and corresponding probabilities to observe the Law of Large Numbers. Simulated experiments involve tossing a coin, spinning a spinner, and observing the gender of children i...
https://education.ti.com/en/activity/detail/probability-simulations_1

Probability Distributions

Students list outcomes for probability experiments such as flipping a coin, rolling number cubes, and observing the sex of each child born in a family. They use these outcomes to record the values of random variables, such as number of tails, sum of the cubes, and number of boys. Students then cr...
https://education.ti.com/en/activity/detail/probability-distributions_2

Probability Distributions

Students will describe how the distribution of a random sample of outcomes provides information about the actual distribution of outcomes in a discrete sample space.
https://education.ti.com/en/activity/detail/probability-distributions_1

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

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

Monopoly and Regression

This lesson involves analyzing the association between the number of spaces from Go and the cost of the property on a standard Monopoly board.
https://education.ti.com/en/activity/detail/monopoly-and-regression

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