Which were the two important minority population that remained in Catalonia?

the covenant that god made with abraham was a unilateral (one-sided) promise from god to abraham.   apart from anything abraham did, god was promising that he was going to bring about a great nation from abraham's offspring, and that the messiah (meaning "the anointed one") would come from abraham's descendants, as one through whom the whole world would receive favor from god.   as god promised abraham, "through your offspring all nations on earth will be blessed" (genesis 22: 18).

the "new covenant" was announced by jesus of nazareth, who had asserted that he was the "son of david" (and descendant of abraham) that fulfilled those promises to abraham.   when jesus introduced the sacred meal that we now refer to as the lord's supper, as told his disciples in reference to the wine they drank, "this cup is the new covenant in my blood, which is poured out for you" (luke 22: 20).   this "new covenant" through jesus was also a unilateral (one-sided) covenant.   he gave himself in sacrifice for all people, without conditions attached.   as his friend and apostle john later wrote, "he is the atoning sacrifice for our sins, and not only for ours but also for the sins of the whole world" (1 john 2: 2).

so the covenant with abraham and the "new covenant" ushered in by jesus are, in essence, connected as one covenant -- because jesus was saying he was the one promised to abraham that fulfilled that covenant and brought blessing to the world.

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).