Scattered violets - humility, Orange lilies - Passion of the Christ, 3 red carnations - Nails of Christ's crucifixion (apex)
Answer:
The correct answer is: The participants' abilities to solve geometry problems.
Explanation:
Researches contain both dependent and independent variables.
In a research the dependent variable is the variable that the researcher wants to identify if it changes by modifying the independent variables.
Independent variables are multiple factors that if modified they may or may not change the dependent variable.
In this particular case, Dr Martinez wants to prove the effects of diet on mental alertness. He proceeds to instruct the participants to eat breakfast that's either high in carbohydrates or high in protein (Independent variables) and then Dr. Martinez then measures the participants abilities to solve geometry problems (Dependent variable).
In conclusion, the dependent variable in this study is: Participants' abilities to solve geometry problems.
Answer:
- Effective, but not efficient.
Explanation:
Leadership is associated with a blend of effective as well efficient performance to attain the quality goals within a specified time-limit.
As per the given description, Brenda would be called an <u>'effective, but not efficient'</u> manager as she, however, produced the desired quality results effectively but could not ensure the 'maximum utilization of time'(as she took more time as compared to the other managers). This wastage or not using time efficiently demonstrates that she was effective but not efficient as she failed to employ the resources in the supreme possible manner.
The Type II error would be to conclude that EnerG is no more nutritious than Supreme when Energy actually provides more health benefits.
Option b
<u>Explanation:</u>
Type II error sometimes referred to as beta error is a term in statistics that doesn’t reject the false-null hypothesis. It occurs when one refuses to reject the false null hypothesis. In this type of error, the false findings are accepted as true.
It also confirms two different scenarios as similar even though they are different. It can be reduced by adjusting the criteria of the null hypothesis by increasing tolerance with caution to ensure that the error type doesn’t end up being Type I error.
Answer:
hope it helps...
Explanation:
Similarly, a day with a mean temperature below 20° F is associated with an increase in annual mortality of roughly 0.07–0.08 percent. ... The preferred estimates suggest that climate change will lead to an increase in the age adjusted U.S. mortality rate of 3 percent by the end of the twenty-first century.
