Combinations of Normal Distributions & Sample Mean Distributions (DP IB Applications & Interpretation (AI))

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  • True or False?

    If X subscript 1 comma space X subscript 2 comma end subscript space... comma space X subscript n are independent normal distributions then a subscript 1 X subscript 1 plus a subscript 2 X subscript 2 plus... plus a subscript n X subscript n is also a normal distribution.

    True.

    If X subscript 1 comma space X subscript 2 comma end subscript space... comma space X subscript n are independent normal distributions then a subscript 1 X subscript 1 plus a subscript 2 X subscript 2 plus... plus a subscript n X subscript n is also a normal distribution.

  • If X subscript 1 comma space X subscript 2 comma end subscript space... comma space X subscript n are independent observations of a variable X, write a formula for the distribution of the sample means, X with bar on top.

    If X subscript 1 comma space X subscript 2 comma end subscript space... comma space X subscript n are independent observations of a variable X, then the distribution of the sample means is X with bar on top equals fraction numerator X subscript 1 plus X subscript 2 plus... plus X subscript n over denominator n end fraction.

  • True or False?

    For any distribution, the mean of X with bar on top is equal to the mean of X.

    True.

    For any distribution, the mean of X with bar on top is equal to the mean of X.

  • If a random sample of n observations is taken from a population, X, with variance sigma squared, what is the variance of X with bar on top?

    If a random sample of n observations is taken from a population, X, with variance sigma squared, then the variance of X with bar on top is sigma squared over n.

  • True or False?

    For any sample size, if X is normally distributed then X with bar on top is also normally distributed.

    True.

    For any sample size, if X is normally distributed then X with bar on top is also normally distributed.

  • If a random sample of n observations are taken from X tilde straight N open parentheses mu comma space sigma squared close parentheses, what is the distribution of X with bar on top?

    If a random sample of n observations are taken from X tilde straight N open parentheses mu comma space sigma squared close parentheses, then X with bar on top tilde straight N open parentheses mu comma space sigma squared over n close parentheses.

  • What does the Central Limit Theorem tell you about the distribution of X with bar on top?

    The Central Limit Theorem states that if a large enough sample is taken (>30), then X with bar on top can be approximated by a normal distribution.

  • A large sample of n observations are taken from the distribution X with mean mu and variance sigma squared, describe the distribution of X with bar on top.

    A large sample of n observations are taken from the distribution X with mean mu and variance sigma squared, then by the Central Limit Theorem X with bar on top is approximately straight N open parentheses mu comma fraction numerator space sigma squared over denominator n end fraction close parentheses.

  • True or False?

    If a random sample of 40 observations is taken from X tilde straight N open parentheses mu comma space sigma squared close parentheses, then the Central Limit Theorem is needed to describe X with bar on top.

    False.

    If a random sample of 40 observations is taken from X tilde straight N open parentheses mu comma space sigma squared close parentheses, then the Central Limit Theorem is not needed to describe X with bar on top.

    If X is normally distributed, then X with bar on top is also normally distributed for any sample size.

  • What is a confidence interval for the population mean?

    A confidence interval for the population mean is created using a sample of a population.

    It is an interval of values around the sample mean for which there is a specific probability that it contains the population mean.

  • What is meant by the confidence level of a confidence interval for the population mean?

    The confidence level of a confidence interval for the population mean is the proportion of such confidence intervals expected to contain the population mean.

  • When should you use a normal distribution for a confidence interval (z-interval)?

    You should use a normal distribution for a confidence interval (z-interval) when the population variance, sigma squared, is known.

  • When should you use a t-distribution for a confidence interval (t-interval)?

    You should use a t-distribution for a confidence interval (t-interval) when the population variance, sigma squared, is unknown.

  • True or False?

    Increasing the confidence level decreases the width of the confidence interval.

    False.

    Increasing the confidence level increases the width of the confidence interval.

    To have more likelihood that the interval contains the mean, the interval must be bigger.

  • True or False?

    Increasing the sample size decreases the width of the confidence interval.

    True.

    Increasing the sample size decreases the width of the confidence interval.

    The bigger the sample size, the more precise the confidence interval.

  • It is claimed that the mean of a population is mu subscript 0.

    A 95% confidence interval is constructed and mu subscript 0 is outside the interval.

    Is there sufficient evidence to reject the claim?

    It is claimed that the mean of a population is mu subscript 0.

    A 95% confidence interval is constructed and mu subscript 0 is outside the interval.

    There is sufficient evidence to reject the claim.

  • Three samples are used to create 95% confidence intervals for the population mean.

    How would you find the probability that all three confidence intervals contain the population mean?

    Three samples are used to create 95% confidence intervals for the population mean.

    The probability that all three confidence intervals contain the population mean is 0.95 cubed.