Differences between statistical mean and statistical proportion (with example)? Does statistical proportion p only work with...
Differences between statistical mean and statistical proportion (with example)? Does statistical proportion p only work with categorical data and not with numerical data? Is Maximum Likelihood Estimation (e.g to find the parameter value that yields the biggest probability) only used to quantify the statistical proportion p?
Homework Answers
Difference between Statistical mean and Statistical Proportion: Statistical mean is the average value of a sample while the sample proportion is amount of the sample that shares a commonality relative to its whole. They can both be used as estimates of the population they are sampled from they just tell us slightly different information.
Example: average may tell us roughly how many people agree with a topic, while the proportion tke a value from 0 to 1 saying exactly how many people from the sample of agreers and disagreers.
As proportion means portion or group that represents a pert of whole. If Numerical data devides into groups then that Particular groups represent proportion so Proportion also represent numerical dat also.
Its not necessary that only MLE used to find estimation , chi- square also used for estimation method used in categorical data estimation.
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Differences between statistical mean and statistical proportion
(with example)? Does statistical proportion p only
work with...
Selecting a random sample is an example of a statistical experiment, and the sample statistic p i...
Selecting a random sample is an example of a statistical experiment, and the sample statistic p is a numerical description of the result of the experiment. Therefore, p is a random variable. The probability distribution of p is called the sampling distribution of p In practice, you select one random sample and use the information from that sample to estimate the population parameter of interest. However statisticians sometimes perform a procedure called repeated sampling, in which the experiment is run...
Is there any example that MLE is used to estimate the sample mean (please give one...
Is there any example that MLE is used to estimate the sample mean (please give one if there is)? Usually I only see MLE is used to estimate sample proportion p to maximize some probability? Does MLE only need one random sample to estimate the parameter while bootstrapping you can take many random samples as you want? What is the difference between these two methods?
J This question relates to the idea of maximum likelihood estimation (MLE). MLE is a commonly...
J This question relates to the idea of maximum likelihood estimation (MLE). MLE is a commonly used method in statistics, if not a cornerstone, that finds estimates of model parameters by answering the question, "given some observed data, what are the parameter estimates that maximise the likelihood (chance) of observing that data in the first place?" To provide an example, if we observe the values 2.6, 3.2 and 5.1 assumed to be drawn independently from the same distribution, it is...
Concept Check: Terminology 0/3 points (graded) Suppose you observe iid samples X1,…,Xn∼P from some unknown distribution...
Concept Check: Terminology
0/3 points (graded)
Suppose you observe iid samples X1,…,Xn∼P from some
unknown distribution P. Let F denote a parametric
family of probability distributions (for example, F could be the
family of normal distributions {N(μ,σ2)}μ∈R,σ2>0).
In the topic of goodness of fit testing, our
goal is to answer the question "Does P
belong to the family F, or is P
any distribution outside of F
?"
Parametric hypothesis testing is a particular case of goodness
of fit testing...
26. ____ In analysis of variance, observed mean differences appear, somewhat disguised, as variability a) between...
26. ____ In analysis of variance, observed mean differences appear, somewhat disguised, as variability a) between groups b) between subjects c) within groups d) within subjects 27. ____ When all possible difference between pairs of population means are evaluated not with F test, but a series of regular t tests, the probability of a a) type I error is larger than the level of significance b) type I error is smaller than the level of significance c) type II error...
Can you solve Question 4.1.3 with details? This is from Advanced Statistics. 236 Some Statistical Inferences...
Can you solve Question 4.1.3 with details? This is from Advanced
Statistics.
236 Some Statistical Inferences the histogram. Use the R function dganna(X, 8hape. 1,scale-のto evaluate the plf. (c) Obtain the sample median of the data, which is an estimate of the median lifetime of a motor. What parameter is it estimating Le., determine the nedian of x)? (d) Based oa the mle, what is another estimate of the median of X? .1.2. Here are the weights of 26 professional...
1. A ________ is a sample statistic such as the mean or a proportion that serves...
1. A ________ is a sample statistic such as the mean or a proportion that serves as an estimate of the same value in the population. population parameter confidence level point estimate confidence interval standard error of the mean 2. we can differentiate among variables in terms of their levels of measurement, or the mathematical nature of the values of a variable. For example, the values of a variable measured at the __________ level have an inherent rank order with...
9. P( mean wait is between 11.6 and 13.6)= Explain how to found your answer. 10....
9. P( mean wait is between 11.6 and 13.6)=
Explain how to found your answer.
10. A class has 8 students who are assigned seating by lot.
What is the probability that the students will be arranged in order
from shortest to tallest? (Assume that no two students are the same
height.)
11. Minimum sample size ___
Show your work
12. Probability ___
Explain how you found the answer
Solve the problem. Points: 5 9) The weights of the fish...
Will rate!! Show good work plz! Only need help on problems that do NOT involve R...
Will rate!!
Show good work plz!
Only need help on problems that do NOT involve R
simulation
Part 3. (13 points) Simulation of Gamma Random Variables Background: When we use the probability density function to find probabilities for a random variable, we are using the density function as a model. This is a smooth curve, based on the shape of observed outcomes for the random variable. The observed distribution will be rough and may not follow the model exactly. The...
Assume a researcher wants to see if there are mean differences in body image between those who ex...
Assume a researcher wants to see if there are mean differences in body image between those who exercise in the front of an aerobic dance class vs. those who exercise at the back of the class. The researcher also wants to determine if the findings depend on whether the participants are male or female. What is the DV? What is the IV or IVs? How many levels of each IV? What are the three research questions that will be asked?...
Selecting a random sample is an example of a statistical experiment, and the sample statistic p is a numerical description of the result of the experiment. Therefore, p is a random variable. The probability distribution of p is called the sampling distribution of p In practice, you select one random sample and use the information from that sample to estimate the population parameter of interest. However statisticians sometimes perform a procedure called repeated sampling, in which the experiment is run...
J This question relates to the idea of maximum likelihood estimation (MLE). MLE is a commonly used method in statistics, if not a cornerstone, that finds estimates of model parameters by answering the question, "given some observed data, what are the parameter estimates that maximise the likelihood (chance) of observing that data in the first place?" To provide an example, if we observe the values 2.6, 3.2 and 5.1 assumed to be drawn independently from the same distribution, it is...
Concept Check: Terminology
0/3 points (graded)
Suppose you observe iid samples X1,…,Xn∼P from some
unknown distribution P. Let F denote a parametric
family of probability distributions (for example, F could be the
family of normal distributions {N(μ,σ2)}μ∈R,σ2>0).
In the topic of goodness of fit testing, our
goal is to answer the question "Does P
belong to the family F, or is P
any distribution outside of F
?"
Parametric hypothesis testing is a particular case of goodness
of fit testing...
Can you solve Question 4.1.3 with details? This is from Advanced
Statistics.
236 Some Statistical Inferences the histogram. Use the R function dganna(X, 8hape. 1,scale-のto evaluate the plf. (c) Obtain the sample median of the data, which is an estimate of the median lifetime of a motor. What parameter is it estimating Le., determine the nedian of x)? (d) Based oa the mle, what is another estimate of the median of X? .1.2. Here are the weights of 26 professional...
9. P( mean wait is between 11.6 and 13.6)=
Explain how to found your answer.
10. A class has 8 students who are assigned seating by lot.
What is the probability that the students will be arranged in order
from shortest to tallest? (Assume that no two students are the same
height.)
11. Minimum sample size ___
Show your work
12. Probability ___
Explain how you found the answer
Solve the problem. Points: 5 9) The weights of the fish...
Will rate!!
Show good work plz!
Only need help on problems that do NOT involve R
simulation
Part 3. (13 points) Simulation of Gamma Random Variables Background: When we use the probability density function to find probabilities for a random variable, we are using the density function as a model. This is a smooth curve, based on the shape of observed outcomes for the random variable. The observed distribution will be rough and may not follow the model exactly. The...
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