BTC/USDT Terminshandelsanalys - 08 03 2025
BTC/USDT Futures Handelsanalys - 08 03 2025
1. Marknadsöversikt
Per den 8 mars 2025 visar BTC/USDT futuresmarknaden tecken på baisseartad momentum. Det aktuella spotpriset är $86,038.14, medan futurespriset är något lägre på $85,986.80, vilket indikerar en liten backvärring. Marknaden har upplevt en 24-timmars förändring på -2.47%, med ett intraday högt på $91,100.00 och ett lågt på $85,218.47. Denna prisrörelse tyder på ökad volatilitet och potentiellt nedåtgående tryck.
2. Teknisk Analys
De tekniska indikatorerna målar en baisseartad bild för BTC/USDT futures:
- **Glidande Medelvärden (MA/EMA):** Det 50-dagars Glidande Medelvärde (MA) är på $88,821.70, medan det 50-dagars Exponentiellt Glidande Medelvärde (EMA) är på $88,083.85. Båda ligger över det aktuella priset, vilket indikerar en baisseartad trend.
- **Relative Strength Index (RSI):** RSI (14) är på 24.00, vilket är djupt i översåld territoriet. Även om detta kan signalera en potentiell vändning, indikerar det också starkt säljtryck.
- **MACD:** MACD är på -752.89, med signallinjen under# 7.3: The Research Hypothesis and the Null Hypothesis
- Page ID - 19570
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Hypotheses are predictions of expected findings.
- The Research Hypothesis
A research hypothesis is a mathematical way of making a prediction about what the researchers expect to happen in a study. This prediction is based on prior knowledge of how variables typically behave, and thus it is an educated guess. However, because the prediction is mathematical, it must be written very precisely. Let’s use a previous example to see how this works.
In the “Animal Research” case study from the start of this chapter, the topic was whether or not animal research is ethical. The example study was to determine whether or not the public believes that animal research is necessary. In this case, researchers would predict that the majority of the public would answer yes, that animal research is necessary. But how do we make that prediction mathematical?
If the researchers are making a prediction about what the public believes, they are making a prediction about population proportions. We learned in the last chapter that proportions are associated with categorical variables, and that the correct parameter to describe the distribution of categorical variables is \(𝑝\). In this case, the specific hypothesis is that the majority of the public believes that animal research is ethical. In other words, in the population, the proportion of people who believe that animal research is ethical is greater than 0.50. We will use 0.50 because that indicates half (or 50%) of the population. We can write our research hypothesis as:
\(H_{1}\): \(p>0.50 \)
The letter \(H\) stands for hypothesis, and the subscript 1 indicates that this is our first (and only) research hypothesis. The letter \(p\) indicates the population parameter, and the expression \(p > 0.50\) indicates our prediction that the proportion of the population who believe that animal research is ethical is greater than 50%. Taken together, this expression \(H_{1}\): \(p > 0.50\) means that we are predicting that the proportion of the population who believe that animal research is ethical is greater than 50%. When we express our predictions mathematically like this, we can use statistical tools to estimate the probability of our predictions being accurate.
- The Null Hypothesis
The research hypothesis is only half of the analysis. The other half is the null hypothesis. The null hypothesis is also a prediction about the population, but it is exactly the opposite prediction of the research hypothesis. In this case, the null hypothesis would be that the proportion of the population who believe that animal research is ethical is not greater than 50%. In other words, the null hypothesis is that the proportion of the population who believe that animal research is ethical is 50% or less. We can write the null hypothesis as:
\(H_{0}\): \(p \leq 0.50\)
Again, the letter \(H\) stands for hypothesis, and the subscript 0 indicates that this is the null hypothesis. The letter \(p\) indicates the population parameter, and the expression \(p \leq 0.50\) indicates our prediction that the proportion of the population who believe that animal research is ethical is 50% or less. Taken together, this expression \(H_{0}\): \(p \leq 0.50\) means that we are predicting that the proportion of the population who believe that animal research is ethical is 50% or less.
In science, we never say that we “prove” anything. Instead, we say that our data either “support” or “do not support” our hypotheses. This is because we are dealing with probabilities. We can say that our data support our research hypothesis, but there is always a chance that we are wrong. Similarly, we can say that our data do not support our null hypothesis, but there is always a chance that we are wrong. This is why we never say that we “prove” anything in science.
We can think about it like a criminal trial. In a criminal trial, the defendant is innocent until proven guilty. The null hypothesis is that the defendant is innocent, and the research hypothesis is that the defendant is guilty. The jury can either find the defendant guilty or not guilty. If the jury finds the defendant guilty, they are saying that the data support the research hypothesis. If the jury finds the defendant not guilty, they are saying that the data do not support the research hypothesis. However, the jury can never say that the defendant is innocent. They can only say that the defendant is not guilty. This is because there is always a chance that the jury is wrong. Similarly, in science, we can never say that our data prove our research hypothesis. We can only say that our data support our research hypothesis.
- Summary
The research hypothesis is a mathematical prediction about what the researchers expect to happen in a study. The null hypothesis is exactly the opposite prediction of the research hypothesis. In science, we never say that we “prove” anything. Instead, we say that our data either “support” or “do not support” our hypotheses.
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