Enter your variables — get properly formatted null (H₀) and alternative (H₁) hypotheses with symbolic notation and suggested statistical tests.
A research hypothesis is a testable, falsifiable statement about the expected relationship between variables. Every quantitative study needs at least one pair: a null hypothesis (H₀) stating no relationship exists, and an alternative hypothesis (H₁) stating the relationship you expect to find.
The null hypothesis is what you attempt to REJECT through your statistical analysis. If your p-value is below your significance level (usually 0.05), you reject H₀ and accept H₁. If not, you "fail to reject" H₀ — you never "accept" or "prove" the null.
A good hypothesis is specific (names exact variables), testable (can be measured), directional when possible (states which way the relationship goes), and grounded in theory or prior research.
Specifies the direction: "X increases Y" or "X decreases Y". Use when prior research suggests a specific direction.
"Students who use social media >3 hours daily will have lower GPA than those who use it <1 hour."
States a relationship exists without specifying direction. Use when you're unsure which way the effect goes.
"There is a significant relationship between social media usage and academic performance."
The "default" — states no relationship, no difference, no effect. This is what your statistical test attempts to reject.
"There is no significant relationship between social media usage and academic performance."
What you actually believe is true — the relationship you expect your data to support. Accepted when H₀ is rejected.
"There is a significant negative relationship between social media usage and academic performance."
Typically one pair (H₀ + H₁) per research question. If you have 3 research questions, you'll have 3 null and 3 alternative hypotheses. Some studies have 5-7 pairs.
Usually no. Qualitative research is exploratory and uses research questions rather than hypotheses. Hypotheses are primarily for quantitative and some mixed-method studies.
They're the same thing — both represent the alternative hypothesis. H₁ is more common in some fields, Ha in others. Use whichever your university/department prefers.
Directional if prior research strongly suggests a specific direction. Non-directional if you're exploring a new relationship or prior research shows mixed results. When in doubt, go non-directional — it's more conservative.
No. Hypotheses must be stated BEFORE data collection (pre-registration). Changing hypotheses after seeing your data is called HARKing (Hypothesizing After Results are Known) and is considered a questionable research practice.