Answer: C. Educating women
Explanation: It could be argued that, High rate of fertility can result due to economic and societal roles and contribution of children.
High infant mortality rate, which is generally referred to as the death of children under the age of one.
Religious pressure is also a contributing factor as some religion are of the opinion that favors Hugh child bearing rate.
The societal conception or desire for male children in some societies is another reason for high fertility.
However, female education is not a reason for high fertility rate as female education will only explain and educate female on the best way to go about fertility a disease childbearing.
Benefits- Keep in touch, stay informed
Negatives- Risk of cyber bullying, risk becoming addicted, procrastination
You could miss out on relationships, times to hang out with others, etc
Answer:
Engaging in less physical activity.
Explanation:
Health-related behaviors: This refers to practices, activities or personal attributes, and habits that can put at risk or enhance the overall performance of the participants including mental, psycho-social, and physical well-being.
Examples: Physical activity, diet, coping with stressful events, and sleep are the factors that can get affected by health-related behaviors.
Answer:
Those who supported the Constitution and a stronger national republic were known as Federalists. Those who opposed the ratification of the Constitution in favor of small localized government were known as Anti-Federalists.
Explanation:
The answer is <u>"c. a confounding variable is an explanatory variable that was considered in a study whose effect cannot be distinguished from a second explanatory variable in the study."</u>
A confounding variable is an outside impact that progressions the impact of a dependent and independent variable. This superfluous impact is utilized to impact the result of an exploratory plan. Just, a confounding variable is an additional variable went into the condition that was not represented. Confounding variables can destroy an analysis and deliver pointless outcomes. They propose that there are connections when there truly are most certainly not. In an examination, the independent variable by and large affects the dependent variable.