Answer:
Today you can walk into your local grocery store and fill your shopping cart with a variety of fresh produce. Then, with no more effort than it takes to push your cart, you can head to the cereal aisle to pick out your favorite boxes of breakfast cereal before ending your shopping trip in the bread aisle, where you grab a couple of loaves of bread for your lunchtime sandwiches. What you probably don't realize is that these conveniences that you experience today, could not be a reality if it were not for the Agricultural Revolution that took place hundreds of years ago. In this lesson, we will take a look at how advancements in farming techniques and equipment that happened during the Agricultural Revolution changed our lives, and how they have impacted our environment.The development of agriculture is responsible for the shift from a nomadic lifestyle to one of settlements that later became urban environments. As well, this development has had a significant effect on human society. As agriculture changed from the natural environment, such as picking wild berries, to that of tilled fields and pastures, growing crops became a selective process. Farming procedures allowed for a greater variety of crops that were healthier and more diverse.
Explanation:
https://www.enotes.com/homework-help/how-did-development-agriculture-bring-change-human-791733
https://study.com/academy/lesson/agricultural-and-industrial-revolutions-impacts-on-the-environment.html
check these websites
they can help
Well the deadliest disaster in US history was in 1900, from the tropical Galveston cyclone in texas, which caused 6,000-12,000 deaths and around $28,000,000 in damage. Only 6 years later, the second deadliest disaster was the 1906 San Francisco hurricane and fire which claimed over 3,000 deaths.
Answer:
I think that the answer is A
Explanation:
The answer is A
Yes, data is reliable for predicting the future because if you think about weather forecasts they use a huge chart of data to help foresee what the weather will be for the day after, the week after, and etc. This is only one of the examples for data being reliable. Especially if it's fastdata, actionable data, and so on.
