Coffee is good, then bad, then good
Every week reverses the last and you have stopped believing any of it.
Make sense of science in the news without a science degree.
Match the conclusion to the study design, population, comparison and uncertainty. A result can be informative without proving a cause, and a large sample does not repair a biased comparison. Start by reconstructing what was actually measured.
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A starting goal
I want to understand how scientific studies support a claim. Teach me about experiments, correlation, uncertainty, and replication so I can make better sense of science in the news.
Change any word so it fits your situation. The course is built from what you type and a few setup questions.
Start today
Useful on their own. The course is for when you want the whole skill, not just the first move.
In a fictional study, sixteen of twenty people who chose a study app passed a quiz, compared with twelve of twenty who did not choose it. The observed rates are 80% and 60%, a difference of twenty percentage points. These are teaching numbers, not Cadence results.
Does this prove the app caused the difference? No. The groups chose differently and may already differ in prior knowledge, study time or motivation. The numbers describe an association in these groups. They do not tell us what would have happened to the same learners without the app.
Look for how people entered groups, their starting points, missing outcomes, the exact quiz and uncertainty. Random assignment can strengthen a causal comparison, but execution still matters. Observational research can also contribute to causal reasoning with appropriate designs and assumptions. Repetition adds useful evidence only when the methods and findings withstand scrutiny.
Before the course is built
Lesson 1 opens on the moment you describe, and the examples use your role. For this request, expect questions like these.
Right for now
Every week reverses the last and you have stopped believing any of it.
Sample size, control group and p-value are words without weight.
Some findings deserve belief and some do not, and you would like to tell which.
Course arc
Cadence writes the lessons for you, so the exact path follows your answers. This is the ground a course built from this sentence covers.
01 / 06Hypotheses, evidence and provisional conclusions.
Compare experiments, cohorts and surveys, including the assumptions each conclusion needs.
Why they differ, and the ways researchers try to bridge them.
Sample size, error bars and what significant does and does not mean.
Examine whether a repeated finding survives suitable methods and different contexts.
Tracing a news claim back to the study and judging it.
What changes
Know what an experiment, a survey and an observational study can each establish.
Tell association from cause, and know what an error bar is telling you.
Evaluate a headline with a short checklist.
The comparison must address plausible alternative explanations. Selection, measurement problems and missing data can still matter.
Quality, independence, consistency and applicability matter. Confidence can increase while limitations and uncertainty remain.
Course questions
Calculate an invented result. In a fictional study, sixteen of twenty people who chose a study app passed a quiz, compared with twelve of twenty who did not choose it. The observed rates are 80% and 60%, a difference of twenty percentage points. These are teaching numbers, not Cadence results. Test the causal headline. Does this prove the app caused the difference? No. The groups chose differently and may already differ in prior knowledge, study time or motivation. The numbers describe an association in these groups. They do not tell us what would have happened to the same learners without the app. Ask what a stronger account would report. Look for how people entered groups, their starting points, missing outcomes, the exact quiz and uncertainty. Random assignment can strengthen a causal comparison, but execution still matters. Observational research can also contribute to causal reasoning with appropriate designs and assumptions. Repetition adds useful evidence only when the methods and findings withstand scrutiny.
No. Cadence builds the course when you type the sentence and answer a few setup questions, so the lessons follow your situation. This page describes what a course built from this request covers. You see the whole path before Lesson 1.
Match the conclusion to the study design, population, comparison and uncertainty. A result can be informative without proving a cause, and a large sample does not repair a biased comparison. Start by reconstructing what was actually measured. It sits under Science & nature in the Ideas & discovery part of the library.
No. Setup asks what you already know and where you want to use it, and the course starts from there. Bring a real situation if you have one; the examples are built around it.
Most courses run 7 to 30 lessons. The course length is sized to what you asked for. You set the pace: one lesson at a time, as often as you like. Lessons can be read or played as audio.
No. Cadence is for practical self-learning and does not award accredited degrees or professional certification.
Start today
A starting goal
I want to understand how scientific studies support a claim. Teach me about experiments, correlation, uncertainty, and replication so I can make better sense of science in the news.
Want new features first?