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Inference for Means

by David Spade, PhD
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    About the Lecture

    The lecture Inference for Means by David Spade, PhD is from the course Statistics Part 2. It contains the following chapters:

    • Inference for Means
    • The t-Distribution
    • Three Conditions
    • Using Margin of Error
    • Pitfalls to Avoid

    Included Quiz Questions

    1. The distribution of the sample mean is more closely normal with larger sample sizes.
    2. The distribution of the sample mean is more normal with smaller sample sizes.
    3. In order for the Central Limit Theorem to apply, the population must be normal.
    4. The standard deviation of the sample mean increases as the sample size increases.
    1. The population standard deviation must be known.
    2. The data must come from a normal population.
    3. The population standard deviation is estimated with the sample standard deviation.
    4. The test statistic is computed in the same way as the z-statistic from previous procedures, but the population standard deviation is estimated.
    1. It has thinner tails than the normal distribution.
    2. It is more peaked than the normal distribution.
    3. It has thicker tails than the normal distribution.
    4. As the degrees of freedom increase, the t-distribution looks more and more like the normal distribution.
    1. The larger the sample size, the more unimodal and symmetric the histogram must look in order to use the t-interval.
    2. The data must come from a random sample.
    3. The data come from a distribution that appears to be unimodal and symmetric, with no outliers or strong skew.
    4. The sample size must be smaller than 10% of the population size.
    1. It is poor practice to use the one-sample t-procedures with non-randomized data.
    2. It is poor practice to watch out for outliers.
    3. It is poor practice to beware of data with multiple modes and strong skew.
    4. It is poor practice to watch out for biased data.

    Author of lecture Inference for Means

     David Spade, PhD

    David Spade, PhD


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