<u>When we make estimates of or draw conclusions about one or more characteristics of a population based upon the </u><u>sample</u><u>, we are using the process of </u><u>statistical inference</u><u>.</u>
- To estimate this sample to sample variance or uncertainty is the goal of statistical inference.
What is the purpose of statistical inferences ?
- To be able to make inferences about a population based on data from a sample is the goal of statistical inference.
- The process of statistical inference involves selecting a sample, gathering data from that sample, calculating a statistic from the data, and drawing conclusions about the population from that statistic.
How is statistical inference used to draw conclusions?
Estimation and hypothesis testing are components of statistical inference (evaluating a notion about a population using a sample) (estimating the value or potential range of values of some characteristic of the population based on that of a sample).
Learn more about statistical inference
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Answer:
The answer is below
Step-by-step explanation:
Since 1000ml Of Dextrose 25% is needed to be produced from Dextrose 70%. Let us assume that x ml of Dextrose 70% is mixed with a Dextrose 5% to get 1000 ml of Dextrose 25%. Hence:
The amount of Dextrose 5% = 1000 ml - x ml = 1000 - x
25% of 1000 ml = 70% of x + 5% of (1000 - x)
25000 = 70x + 5000 - 5x
Simplifying gives:
65x = 25000 - 5000
65x = 20000
x = 308 ml
Therefore 308 ml of Dextrose 70% was mixed with 692 ml of Dextrose 5% to produce 1000 ml of Dextrose 25%.
Answer: 0.0793
Step-by-step explanation:
Let the IQ of the educated adults be X then;
Assume X follows a normal distribution with mean 118 and standard deviation of 20.
This is a sampling question with sample size, n =200
To find the probability that the sample mean IQ is greater than 120:
P(X > 120) = 1 - P(X < 120)
Standardize the mean IQ using the sampling formula : Z = (X - μ) / σ/sqrt n
Where; X = sample mean IQ; μ =population mean IQ; σ = population standard deviation and n = sample size
Therefore, P(X>120) = 1 - P(Z < (120 - 118)/20/sqrt 200)
= 1 - P(Z< 1.41)
The P(Z<1.41) can then be obtained from the Z tables and the value is 0.9207
Thus; P(X< 120) = 1 - 0.9207
= 0.0793
