Answer:
Step-by-step explanation:
Ok, so we have to help your pupil (lets call her Jane) figure out "why researchers should use a random sample to conduct a survey". So, i will list all of the choices.
- A random sample is likely to avoid bias
- In a random sample some members of the population are more likely to be selected than others
- Random samples provide consistency and systematically favor one choice over every other choice in each survey question
- Random sampling will provide a more representative sample of population
- Researchers can use a random sample to draw conclusions about the population
Random sampling is used to get the best average, and not favor any one opinion. For example, if you were trying to figure out the daily spending budget of people, you wouldn't just go to the upper clas part with all the rich people, you would survey from all over the town to get results from all kinds of people. So, the answers are:
- A random sample is likely to avoid bias (because thats exactly what they do)
- Random sampling will provide a more representative sample of population (because they are designed to do that)
- Researchers can use a random sample to draw conclusions about the population (thats why they take the samples)
Hope this helps
- From the table showing in the diagram, Let's pick the data in the first row:
Time = 3 hours
Money earned = $45
- The amount of money Carl earns per hour is calculated as:
3 hours = $45
1 hour = ?
Cross Multiply
1 hour x $45 / 3 hours
= $15
- Let's confirm our answer using the data in the last column
Time = 10 hours
Money earned = $150
The amount of money Carl earns per hour is calculated as:
10 hours = $150
1 hour = ?
Cross Multiply
1 hour x $150 / 10 hours
= $15
Therefore, the amount of money Carl earns per hour is $15
To learn more, visit the link below:
brainly.com/question/1004906
If you do the elimination process, here it is.
- A : Too small
+ B : I think so
- C : I little too big
- D : Way too big
Answer:
The prediction for the number of transistor per IC in 1992 is of 4,194,304,000
Step-by-step explanation:
Moore's law:
Moore's law states that the number of transistors per IC doubles every year.
Format of the function:
Following Moore's law, t years after our initial estimative, the number of transistors per IC will be given by:
In which N(0) is the initial estimate.
The number of transistors per IC in 1972 seems to be about 4,000 (a rough estimate by eye).
This means that 
So
What would you predict the number of transistors per IC to be 20 years later, in 1992?
This is N(20). So
The prediction for the number of transistor per IC in 1992 is of 4,194,304,000
Answer:4p>22
Step-by-step explanation:p is standing for a number
22 needs to be less than four times a number
For example we could fill p in with 8 and it would be 24 which is greater than 22
