Dear Data Scientists. ANOVA is a powerful method. You often mention it in your posts. Sadly, I noticed, that you treat it mostly in the simplest way, while it's far beyond that! Well, Fisher didn't invent it with all those applications in mind, but it turned out, over time, that the procedure can be generalized greatly, constituting one of the most important methods in statistics.
You think you know all about it? ANOVA may surprise you.
You might have wondered, why: - is ANOVA called in so many contexts: to compare means, models, testing contrasts? - why is it called with either F or chi2 test (yes, it's about limiting distribution, but how?) - why is it important to call it with appropriate type of sum of squares (when)? - what is the relationship with LS-Means - what does "joint test" actually means.
You might believe that the Tukey HSD method must agree with the result of F test in ANOVA. / No, it doesn't. Scheffe's does. /
If you pick the right answer, then do a research, you will understand how deep is the rabbit hole.
Dear Data Scientists. ANOVA is a powerful method. You often mention it in your posts. Sadly, I noticed, that you treat it mostly in the simplest way, while it's far beyond that! Well, Fisher didn't invent it with all those applications in mind, but it turned out, over time, that the procedure can be generalized greatly, constituting one of the most important methods in statistics.
You think you know all about it? ANOVA may surprise you.
You might have wondered, why: - is ANOVA called in so many contexts: to compare means, models, testing contrasts? - why is it called with either F or chi2 test (yes, it's about limiting distribution, but how?) - why is it important to call it with appropriate type of sum of squares (when)? - what is the relationship with LS-Means - what does "joint test" actually means.
You might believe that the Tukey HSD method must agree with the result of F test in ANOVA. / No, it doesn't. Scheffe's does. /
If you pick the right answer, then do a research, you will understand how deep is the rabbit hole.
Pinterest (PINS) closed at $71.75 in the latest trading session, marking a -0.18% move from the prior day. This change lagged the S&P 500's daily gain of 0.1%. Meanwhile, the Dow gained 0.9%, and the Nasdaq, a tech-heavy index, lost 0.59%.
Heading into today, shares of the digital pinboard and shopping tool company had lost 17.41% over the past month, lagging the Computer and Technology sector's loss of 5.38% and the S&P 500's gain of 0.71% in that time.
Investors will be hoping for strength from PINS as it approaches its next earnings release. The company is expected to report EPS of $0.07, up 170% from the prior-year quarter. Our most recent consensus estimate is calling for quarterly revenue of $467.87 million, up 72.05% from the year-ago period.
That strategy is the acquisition of a value-priced company by a growth company. Using the growth company's higher-priced stock for the acquisition can produce outsized revenue and earnings growth. Even better is the use of cash, particularly in a growth period when financial aggressiveness is accepted and even positively viewed.he key public rationale behind this strategy is synergy - the 1+1=3 view. In many cases, synergy does occur and is valuable. However, in other cases, particularly as the strategy gains popularity, it doesn't. Joining two different organizations, workforces and cultures is a challenge. Simply putting two separate organizations together necessarily creates disruptions and conflicts that can undermine both operations.
