Statistics_and_Probability_Katabasis_Handson_and_Quiz txt

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import numpy as np
import statistics
A=np.array([9.2,10.7,6.8,9,3.4,5.7,5.7])
print(A.mean())
print(A.median())
print(A.mode())
print(A.stdev())
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__________ provides the summary statistics of data.
Descriptive Statistics
Probability of __________ event is zero.
Impossible
Sample Space is denoted by __________.
S
NumPy package of Python can be used to calculate the mean measure.
True
Central Limit Theorem holds true for __________.
All the options
__________ is the science of learning from data.
Statistics
Probability value always lies between __________ and __________.
0,1
Probability of the sure event is __________.
1
The Acronym ANOVA stands for __________.
Analysis of Variance
The Central Limit Theorem states that as the sample size gets larger, the 
sampling distribution of the sample means approaches a normal distribution.
True
An experiment can be repeated __________.
Infinitely
PMF produces the likelihood of __________ random variable.
Discrete
Expected Value is same as Mean and Average.
True
Probability Density Function produces the likelihood of __________ random 
variable.
Continuous
Central Limit Theorem condition remains true regardless of whether the 
population is skewed or normal, provided the sample size is sufficiently large. 
What is the minimum size of sample to hold this condition?
30
The sum of probability of an event and its complementary is __________.
1
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Common Methods in Inferential Statistics are ________________________.
All the options
Sample Space is a subset of an Event.
False
Measures of Spread include(s)
Range, Standard Deviation, Variance
__________ maps outcomes of an experiment with numerical values.
Random Variables
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