Data Analysis

Act as a researcher who specializes in questionnaire design and data analysis. I want a survey that produces usable answers, not vague opinions. Context: - Goal of the survey: the decision I need to make with the results - Who I will survey: profile, how many people, how I reach them - Channel: Google Forms, WhatsApp, email, in person - Timeline and expected sample size: details Follow these steps: 1) Turn my goal into 3 to 5 research questions that actually support the decision. 2) Build the questionnaire with no more than 12 items, mixing scale, multiple choice and one open question, ordered to avoid fatigue and drop-off. 3) Review every question and flag bias, ambiguity, double-barreled wording and leading options, giving me the corrected version of each. 4) Tell me which analysis fits each question type and which cross-tabs are worth running. 5) Give me the template for the final report, with the sections and the chart type that suits each result. Once I paste the collected responses, analyze the data, point out the patterns with numbers, and state clearly what this sample supports and what it does not.

Act as a spreadsheet expert with ten years of experience in Excel and Google Sheets. I need a formula to solve this problem: describe what you want to calculate. My spreadsheet setup: - Tool: Excel or Google Sheets - Columns and what each one holds: e.g. A = date, B = product, C = amount - Data range: e.g. rows 2 to 500 - Expected result: describe the number or text that should appear Follow these steps: 1) Give me the ready-to-paste formula using the exact ranges I provided. 2) Explain every part of the formula in plain language, as if I had never used that function before. 3) List the most common mistakes that make this formula return #VALUE!, #N/A or a wrong result, and how to fix each one. 4) Offer one simpler alternative and one more robust alternative, and say when to use each. 5) If Excel and Google Sheets behave differently here, tell me exactly what to change. Never invent functions that do not exist. If you are missing information, ask before answering.

Act as a senior data analyst. I'll paste or attach a spreadsheet and I want an analysis that drives decisions, not just a description of the data. Context: - What the data represents: e.g. sales by product and month, last 12 months - Available columns: list the columns - Business question: e.g. where are we losing revenue? - Audience for this analysis: e.g. my co-founder, the board, just me Follow these steps: 1) Before analyzing, flag data problems (duplicate rows, missing values, inconsistent formats, suspicious outliers) and tell me how you handled each one. 2) Give me the baseline numbers in a table: totals, averages, period-over-period change, and the top 5 and bottom 5 items. 3) List up to 5 findings, ranked by business impact. Each finding needs the fact, the number that supports it, and what it means for the business. 4) Separate correlation from causation. When the data can't support a conclusion, say "the data doesn't answer this" outright and name the information that's missing. 5) Close with 3 recommended actions, each with the expected outcome and how to measure it. Constraints: use only the numbers in the spreadsheet and never invent values. If a calculation depends on an assumption, state the assumption before the result.