which of the following distributions can be completely described by only two parameters? a. uniform b....
which of the following distributions can be completely described by only two parameters?
a. uniform
b. normal
c. log normal
d. all of the other choices
Homework Answers
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which of the following distributions can be completely described
by only two parameters?
a. uniform
b....
1.Which of the following distributions is widely used to describe the time between random events? Uniform...
1.Which of the following distributions is widely used to describe the time between random events? Uniform distribution Exponential distribution Poisson distribution Normal distribution None of the answer choices is correct. 2. Which of the following distributions is not skewed? Normal distribution Uniform distribution Lognormal distribution Exponential distribution I only II only III only IV only Only I and II
The uniform, normal, and exponential distributions a. are all continuous probability distributions. b. are all discrete...
The uniform, normal, and exponential distributions a. are all continuous probability distributions. b. are all discrete probability distributions. c. are all the same distributions. d. can be either continuous or discrete, depending on the data.
Univariate Gaussians or normal distributions have a simple representation in that they can be completely described...
Univariate Gaussians or normal distributions have a simple representation in that they can be completely described by their mean and variance. These distributions are particularly useful because of the central limit theorem, which posits that when a large number of independent random variables are added, the distribution of their sum is approximated by a normal distribution. In other words, normal distributions can be applied to most problems Recall the probability density function of the Univariate Gaussian with mean and variance...
Which of the following distributions is considered the cornerstone distribution of statistical inference? a. Poisson distribution...
Which of the following distributions is considered the cornerstone distribution of statistical inference? a. Poisson distribution b. Normal distribution c. Geometric distribution d. Binomial distribution e. Uniform distribution
7 SAMPLING DISTRIBUTIONS (31) Sampling distributions describe the behaviour of population parameters in repeated sam pling...
7 SAMPLING DISTRIBUTIONS (31) Sampling distributions describe the behaviour of population parameters in repeated sam pling (1) True. (2) False (32) Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of will be exactly normal. (4) If the...
Give your own example of a situation in which each of the following distributions would apply...
Give your own example of a situation in which each of the following distributions would apply and explain how it fits the distribution: a. Uniform distribution b. Normal distribution c. Binomial distribution d. Normal approximation of the binomial distribution
When 2 uniform distributions are averaged, the resulting histogram represents this type of shape: A) Uniform...
When 2 uniform distributions are averaged, the resulting histogram represents this type of shape: A) Uniform B) Triangular C) Bell Curve (Normal Distribution) D) Exponential
48. Which of the following descriptions of confidence intervals is correct? a. Confidence intervals can only...
48. Which of the following descriptions of confidence intervals is correct? a. Confidence intervals can only be computed for the mean b. We can only use the normal distribution to compute confidence intervals c. Confidence intervals can be computed for various parameters d. Confidence intervals can only be computed for the population
12 marks Let independent random samples of sizes n and n2 be taken respectively from two normal distributions with unkn...
12 marks Let independent random samples of sizes n and n2 be taken respectively from two normal distributions with unknown means 1 and 2 and unknown variances oand o. Denote the two samples by . . ,Jn, and y,... , yn2: Which have means T and T, and sample variances s and s2, respectively (a) 4 marks Show that when of = o2, the likelihood ratio test statistic for testing Ho 12 against H 2 can be written as T2...
help me on my hw plz Which of the following regarding the student t-distributions is/are not...
help me on my hw plz
Which of the following regarding the student t-distributions is/are not true? 1. Like the standard normal distribution, the t-distribution is centered at 0. II. The spread of a t-distribution is slightly less than the corresponding normal distribution III. At-distribution can be used when the population standard deviation is unknown (A) I only (B) Il only (C) I and III (D) I, II, and III
Univariate Gaussians or normal distributions have a simple representation in that they can be completely described by their mean and variance. These distributions are particularly useful because of the central limit theorem, which posits that when a large number of independent random variables are added, the distribution of their sum is approximated by a normal distribution. In other words, normal distributions can be applied to most problems Recall the probability density function of the Univariate Gaussian with mean and variance...
7 SAMPLING DISTRIBUTIONS (31) Sampling distributions describe the behaviour of population parameters in repeated sam pling (1) True. (2) False (32) Which of the following statements concerning sampling is false? (1) The Central Limit Theorem is very important for statistical inference. (2) The standard error of an estimator is the standard deviation of a statistic. (3) Regardless of the sample size n, if the population distribution is normal then the sampling distribution of will be exactly normal. (4) If the...
12 marks Let independent random samples of sizes n and n2 be taken respectively from two normal distributions with unknown means 1 and 2 and unknown variances oand o. Denote the two samples by . . ,Jn, and y,... , yn2: Which have means T and T, and sample variances s and s2, respectively (a) 4 marks Show that when of = o2, the likelihood ratio test statistic for testing Ho 12 against H 2 can be written as T2...
help me on my hw plz
Which of the following regarding the student t-distributions is/are not true? 1. Like the standard normal distribution, the t-distribution is centered at 0. II. The spread of a t-distribution is slightly less than the corresponding normal distribution III. At-distribution can be used when the population standard deviation is unknown (A) I only (B) Il only (C) I and III (D) I, II, and III
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