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2 years ago

Heating chemicals is defined by the process of combustion.

1 answer:

8 0

The statement "Heating chemicals is defined by the process of combustion" is false, combustion is a chemical reaction in which fuels combine with oxygen from the air to release heat.

<h3>What is combustion?</h3>

It is a rapid oxidation process of certain fuel elements, that is, consisting mainly of hydrogen, carbon and sometimes sulfur.

All combustion processes require the participation of an oxidant, mainly oxygen from the air.

It is based on the exothermic chemical reaction of a substance or mixture of substances called fuel.

Therefore, we can conclude that a combustion process is a type of exothermic reaction that causes a rapid oxidation process therefore the statement "Heating chemicals is defined by the process of combustion" is false.

Learn more about the process of combustion here: brainly.com/question/17580726

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Which of the following conditions will create a biased estimator of a population parameter?.

UkoKoshka [18]

The option that represents the conditions that will create a biased estimator of a population parameter is;

D: The expected value of the estimator is not equal to the population parameter.

<h3>Biased and Unbiased Estimators</h3>

Usually in statistics research, there is what we call population parameters and sampling parameters.

The population parameters represent the full pool from which a sample can be taken while the sample parameters are gotten from the sample taken from the population.

Now, a statistic will be referred to as an unbiased estimator of a population parameter if the mean of the sampling distribution of the statistic is equal to the value of the population parameter.

In contrast to an unbiased estimator, a biased estimator of a population parameter is referred to as such if the mean of the sampling distribution of the statistic is not equal to the value of the population parameter.

The missing options are;

A. The sampling distribution of the estimator is skewed to the left.

B. The sampling distribution of the estimator is skewed to the right.

C. The sampling distribution of the estimator is not the same shape as the distribution of the population parameter.

D. The expected value of the estimator is not equal to the population parameter.

E. The variability of the sampling distribution of the estimator is not equal to the variability of the population parameter.

Read more about biased estimators at; brainly.com/question/7301139

7 0

2 years ago

Which mathematical word describes both 27 x and 6 x in the expression 27 x + 6 x ?

dangina [55]

Commutative is it i think

4 0

1 year ago

Identify which strategy is likely to result in the greatest increase in the San Joaquin kit fox population. Explain why the stra

STALIN [3.7K]

The strategy that is likely to result in the greatest increase in the San Joaquin kit fox population is strategy one.

<h3>Which change is said to be responsible for the decline of the kit fox population A?</h3>

Habitat destruction and fragmentation is known to be the factor that has led to and has been identified as the most vital cause of the kit fox's decline and it is one that has threatens the species' consistent viability.

So, the human intervention that would most likely protect and keep the kit fox populations is through the Introduction of a species that can be able to act as the new kit fox food source.

Hence, The strategy that is likely to result in the greatest increase in the San Joaquin kit fox population is strategy one.

Learn more about fox population from

brainly.com/question/27948222

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1 year ago

Select the proper internal cooking temperature for each food item

meriva

Answer:

Poultry:145 Seafood: 155 Ground meat: 165 ready to eat food : 135 Whole cut beef and pork :165

Explanation:

There you go hope i helped

8 0

3 years ago

Which of the following statements is FALSE?

TiliK225 [7]

The statement that is FALSE among the given options on hypothesis testing is;

Option D; Reducing the significance level (α) can increase a test's effectiveness.

This is about hypothesis testing.

Let us look at each of the options.

A) When we increase the sample size, it means the testing becomes more sensitive and as such we are more likely to reject the null hypothesis. Thus, it increases the effectiveness.

B) Alpha (α) is defined as the probability of rejecting the null hypothesis. Thus it is the probability of making a Type I error.

C) Expanding the sample size makes the hypothesis test to be more sensitive. That is makes it more likely to reject the null hypothesis when it is false and as such it increases the power of the test.

D) The lower the significance level, the lower the power of the test and as such the lesser the tests effectiveness.

Read more about hypothesis testing at; brainly.com/question/15980493

7 0

2 years ago