What caused the power struggle between Pope Gregory VII and Henry IV?conflict over who could choose the bishopsdisagreement over who should construct monasteriesconflict over who should be crowned the next monarchdisagreement over the required amount of church donations

big fat oof x

due to inefficiency of management, the business plan has failed

idk what right product means but i assume it's this one since this was the last one left after i did the other three

the finance team has misjudged the requirement of business plan and chosen a wrong line of credit

operations risk is when the employees make a mistake

flash floods have damaged all machinery in the main manufacturing

natural disasters include anything ruined in the business by the weather or other disasters such as earthquakes

there have been foreign exchange rate fluctuations

economic risks is when things in the economy changes (like interest rates, currency value). the government has a large part in controlling this

i believe it's that they cared for people. hope this ! : )

a hypothesis is an expected answer to a question, usually based on some theory or prior research. hypothesis testing is a method of determining the viability of a hypothesis. let’s use the us presidential election as an example. there are many hypotheses (questions) about how people feel or whom they will vote for. the only way to know the 100% “truth” about the answers to these questions is to ask every single possible voter – something that is impossible, expensive, time consuming etc. instead, we take samples and use statistics to make “best guesses” about the answer to a particular hypothesis. we never know for sure if our conclusion is right at the time we accept/reject it, but these techniques, when used appropriately can get us close to the truth most of the time (which is a lot better than guessing, flipping coins or throwing darts to get answers).

the tricky part about hypothesis testing is that we have to think somewhat backwards about it – we have to test what is known as the “null hypothesis”. as an example, the hypothesis might be “obama is more popular than romney” while the null hypothesis is “there is no difference in popularity between obama and romney”. we focus on the null hypothesis because it tells us exactly what the expected value of our tests should be (obama popularity = romney popularity) and we can collect data and see if it comes out that way (see next section on “significance”). if it does, then we “accept the null hypothesis” and reject our original hypothesis. if the null hypothesis is disproven, we look at the data to see if our original hypothesis holds (obama> romney).