Using the central limit theorem, what is the distribution of sample means when t

Question

Using the central limit theorem, what is the distribution of sample means when the population distribution is the following?
part (a) rectangular
-uniformly distributed
-evenly distributed
- normally distributed
-positively skewed
-negatively skewed

Part (b) normally distributed
- uniformly distributed
- evenly distributed
- negatively skewed
- positively skewed
- normally distributed

part (c) positively skewed
- normally distributed
- negatively skewed
- positively skewed
- evenly distributed
- uniformly distributed

part (d) nonmodal
- uniformly distributed
- positively skewed
- negatively skewed
- normally distributed
- evenly distributed

part (e) multimodal
- evenly distributed
-negatively skewed
- positively skewed
- uniformly distributed
- normally distributed

part (f) negatively skewed
- positively skewed
- normally distributed
- evenly distributed
- negatively skewed
- uniformly distributed

Explanation / Answer

a) Normally Distributed.

b) Normally distributed.

c) Normally distributed.

d) Normally distributed.

e) Normally distributed.

f) Normally distributed.

CLT- Any distribution which has well-defined mean and variance can be approximated to the normal distribution.

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