Making predictions about your data requires the usage of a hypothesis. They aid data analysts in determining what they want to verify or dispute.
Given,
A senior data analyst requests that a junior data analyst offer two hypotheses for a project involving data analytics.
The rationale for a hypothesis must be explained;
This is,
Hypothesis testing is a sort of statistical reasoning that uses information from a sample to draw conclusions about a population parameter or population probability distribution. The parameter or distribution is initially best guessed.
Here,
A hypothesis seeks to infer something from your data. Data analysts use them to show or refute what they want to prove.
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Answer:
The answer is below
Step-by-step explanation:
The relative frequency is the proportion of a class or interval within a category. It is represented by the formula:
Relative frequency = frequency / total frequency
The percent frequency is the relative frequency expressed in percentage, it is given by the formula:
Percent frequency = Relative frequency × 100%
Using the formulas above, the table is filled:
The total frequency = 39
Class Frequency Relative frequency Percent frequency
12 - 14 2 2/39 = 0.0513 0.0513 × 100% = 5.13%
15 - 17 8 8/39 = 0.2051 0.2051 × 100% = 20.51%
18 - 20 11 11/39 = 0.2821 0.2821 × 100% = 28.21%
21 - 23 9 9/39 = 0.2308 0.2308 × 100% =23.08%
24 - 26 9 9/39 = 0.2308 0.2308 × 100% =23.08%
Class Frequency Relative frequency Percent frequency
12 - 14 2 0.0513 5.13%
15 - 17 8 0.2051 20.51%
18 - 20 11 0.2821 28.21%
21 - 23 9 0.2308 23.08%
24 - 26 9 0.2308 23.08%
Answer:
32
Step-by-step explanation:
(4√2)^2=4^2×(√2)^2
=16×2
=32