Answer: According to Tetlock argument, Expert with good predictive power should be willing to;
• EXPLORE DIVERSE INFORMATION AND ANALYTICAL MODEL
• CHALLENGE CONVENTIONAL WISDOM
• BE COMFORTABLE WITH COMPLEXITY AND UNCERTAINTY.
Therefore option b,c,e is the right answer.
Explanation: The predictive power of a scientist is the power a scientist has to generate a testable prediction, thereby making its theory to be a testable prediction.
For an expert to have good predictive power it must have the ability to explore diverse information and analytical model, because when you explore different information and analyse it in the best form, you will be able to postulate more information and discoveries, which can help you to predict a testable theory. By exploring you are trying to challenge conventional wisdom, of why should this be this?, You may get confused and uncertain at a point. But if he you have a good predictive power, you can be able to absorb it all to achieve your discovery and produce a scientific theory with a predictive power.
Answer:
State constitutions define state and local government finances, as well as the state and municipal tax systems in place and the spectrum of civil freedoms that are guaranteed under state law.
Explanation:
Provide for all forms of state and local government finances, establish the state and local tax systems in force, and prevents the concentration of political power
The general form of an interval estimate of a population mean or population proportion is the <u>point estimate </u>plus or minus the <u>margin of error</u>.
<u>Explanation:</u>
An interval estimate is used to estimate a population parameter by using sample data. The margin of error can be decreased by increasing the sample size. The interval estimate of a population mean or population proportion is the point estimate plus or minus the margin of error.
A convenience sample is used from the members of the population because they are easily accessible. A population proportion defines the percentage value of the population. The sampling distribution represents the probability distribution showing all possible values of the sample mean.
