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Answer:

Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. For example, height and weight are related; taller people tend to be heavier then start short people. Correlation can tell you just how much of the variations in peoples weights is related to their heights.

The way I will describe the value of a data using a correlation is that; The correlation data gives us the relationship between the factors considered.

Correlation is a term in statistics that is used to test the relationships between quantitative variables or categorical variables. This means that Correlation, is a measure of how things are related.

The study of how variables are correlated is called correlation analysis.

Correlations are very useful because if you can find out what relationship variables have, you can make predictions about future behavior.

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Answer:

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Explanation:

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Answer:

Explanation:

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The mean pressure applied to the driver's head during a crash test is not equal for at least one pair of car types (compact, midsize, and full-size cars).

To test whether the mean pressure applied to the driver's head during a crash test is equal for each type of car (compact, midsize, and full-size), we can use a one-way analysis of variance (ANOVA). ANOVA is used to compare the means of three or more groups.

First, let's define the null and alternative hypotheses:

Null hypothesis (H₀): The mean pressure applied to the driver's head is equal for compact, midsize, and full-size cars.

Alternative hypothesis (H₁): The mean pressure applied to the driver's head is not equal for at least one pair of car types.

We will use a significance level (α) of 5% (0.05).

Given the data:

Compact cars: 643, 655, 702

Midsize cars: 469, 427, 525

Full-size cars: 484, 456, 402

Let's calculate the necessary statistics for the ANOVA table:

Compact cars:

Sample mean (X): 666.67

Sample standard deviation (S): 31.18

Midsize cars:

Sample mean (X): 473.67

Sample standard deviation (S): 49.17

Full-size cars:

Sample mean (X): 447.33

Sample standard deviation (S): 41.68

Now, we can proceed with the ANOVA test and calculate the F-statistic and p-value.

The ANOVA table looks as follows:

Source of Variation | Sum of Squares (SS) | Degrees of Freedom (df) | Mean Square (MS) | F-statistic

----------------------- | --------------------- | --------------------- | ---------------- | --------------------

Between Groups | SS_between | k - 1 | MS_between = SS_between / (k - 1) | F = MS_between / MS_within

Within Groups | SS_within | N - k | MS_within = SS_within / (N - k) |

Total | SS_total | N - 1 |

Where:

- k is the number of groups (car types)

- N is the total number of observations

- SS represents the sum of squares

Let's calculate the ANOVA table using the provided data:

Total number of observations (N): 3 groups x 3 observations per group = 9

Number of groups (k): 3

Between Groups:

Mean of all observations (grand mean):

x-cap = (666.67 + 473.67 + 447.33) / 3 = 529.89

SS_between = (3 × ((666.67 - 529.89)² + (473.67 - 529.89)² + (447.33 - 529.89)²))

Within Groups:

SS_within = (2 × (31.18² + 49.17² + 41.68²))

Total:

SS_total = SS_between + SS_within

Now, we can calculate the degrees of freedom (df) for each source of variation:

df_between = k - 1 = 3 - 1 = 2

df_within = N - k = 9 - 3 = 6

df_total = N - 1 = 9 - 1 = 8

Finally, we can calculate the mean squares:

MS_between = SS_between / df_between = 343,640.67 / 2 = 171,820.335

MS_within = SS_within / df_within = 32,533.99 / 6 = 5,422.33167

We have obtained the actual values for the ANOVA calculations. Now we can proceed to calculate the F-statistic and determine whether to reject or fail to reject the null hypothesis.

Now, let's calculate the F-statistic:

F = MS_between / MS_within = 171,820.335 / 5,422.33167 ≈ 31.73

To determine whether to reject or fail to reject the null hypothesis, we need to compare the calculated F-statistic to the critical F-value from the F-distribution table at the given significance level (α = 0.05). However, we need to determine the critical F-value based on the degrees of freedom for the numerator (df_between) and denominator (df_within).

For df_between = 2 and df_within = 6, the critical F-value at α = 0.05 is approximately 5.14.

Since the calculated F-statistic (31.73) is greater than the critical F-value (5.14), we can reject the null hypothesis.

Therefore, we conclude that the mean pressure applied to the driver's head during a crash test is not equal for at least one pair of car types (compact, midsize, and full-size cars).

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Answer:

The answer is participlating.

I apologize if I am incorrect.

Have a nice day!

~ Myaka O.

Answer:

Today, psychology is defined as "the scientific study of behavior and mental processes." Philosophical interest in the human mind and behavior dates back to the ancient civilizations of Egypt, Persia, Greece, China, and India.

Psychology was a branch of the domain of philosophy until the 1860s, when it developed as an independent scientific discipline in Germany.

Psychology as a field of experimental study began in 1854, in Leipzig Germany, when Gustav Fechner created the first theory of how judgments about sensory experiences are made and how to experiment on them. Fechner's theory, recognized today as Signal Detection Theory foreshadowed the development of statistical theories of comparative judgment and thousands of experiments based on his ideas (Link, S. W. Psychological Science, 1995). Later, 1879,Wilhelm Wundt founded in Leipzig, Germany, the first Psychological laboratory dedicated exclusively to psychological research in Germany. Wundt was also the first person to refer to himself as a psychologist (a notable precursor of Wundt was Ferdinand Ueberwasser (1752-1812) who designated himself Professor of Empirical Psychology and Logic in 1783 and gave lectures on empirical psychology at the Old University of Münster, Germany. Other important early contributors to the field include Hermann Ebbinghaus (a pioneer in the study of memory), William James (the American father of pragmatism), and Ivan Pavlov (who developed the procedures associated with classical conditioning).

Explanation:

#keep learning!!

Answer:

15 is correct answer answer

Answer:

False analogy is an argument based on misleading, superficial, or implausible comparisons OR A false analogy is a type of informal fallacy..

1. Human rights are basic rights that belong to all of us simply because we are human. They embody key values in our society such as fairness, dignity, equality and respect. ... Most importantly, these rights give us power and enable us to speak up and to challenge poor treatment from a public authority.

2. On the support of victims of human rights violation, the law should clearly state and express the repercussions of violating human rights. The citizen on the other hand should be well versed with human rights and should report any violator of human rights to the relevant authorities for immediate action to be taken. The community can mobilize and make aware the people of their rights and also allow any victim of human rights violations to face the law and seek justice.

3.Undoubtedly, every Government’s foremost duty is to protect human rights. The Government has all the power and infrastructure such as the constitution, the judiciary, the police, etc.  to do this.  

The Government in India is taking all the measures to protect human rights. Wherever, any violation has happened, the Government has taken action and the offenders were brought to justice.

Answer:

Dual Income

Explanation:

Explanation:

nền kinh tế thị trường định hướng XHCN ở Việt Nam hiện nay

Answer:

...

Explanation:

i don't understand sorry:)

??? please explain further