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Of the four effects on interest rates from an increase in the money supply,the one that works in the opposite direction of the other three is the
Alpha
In statistics, alpha represents the level of significance, the probability of rejecting the null hypothesis when it is actually true, commonly set at 0.05 or 5%.
Beta
In statistics, it often refers to the probability of making a Type II error, or in finance, a measure of how much a stock's price could move in relation to the market.
Type II Error
A statistical error that occurs when a false null hypothesis is not rejected, implying that a true effect is missed.
Type I Error
A mistake wherein a true null hypothesis is incorrectly rejected, commonly termed as a "false positive."
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