DATA AND ANALYSIS

Your data arrives carrying its meaning.

Survey data analysis: SPSS export, weighting, indices

When you open answers in a statistical program, you don't have to define which column belongs to which question, or what each number means. The file already knows. When raw answers are not enough, build your own measurement model: compute an index, balance the sample, and read the difference between groups with confidence intervals.

Everything needed to start analysis in a single package.

A researcher opening the file six months from now will understand every variable immediately, without asking questions.

.sav

Labelled SPSS File

Readable variable names, question labels, value labels, and missing-value codes are already built inside the .sav file. Descriptive variable names are generated automatically by AI.

.txt

Codebook Document

A complete codebook document explaining each variable, its original question wording, measurement scale, and all value codes.

Flow

Survey Flow Plan

A structured flow map documenting which respondent path skipped which questions and how conditional branches were routed.

.csv

Raw Response Table

A clean, UTF-8 CSV table that opens seamlessly in Excel, R, Python, Stata, or your preferred quantitative tool.

As designed in the survey, so structured in the data.

Missing values coded by reason

Empty cells declare why they are empty: skipped due to logic (−99), displayed but left blank (−98), or actively declined (−97). All three are defined as user-missing in SPSS so they never distort mean averages.

Dynamic & paired comparisons

Even when measuring reciprocal attitudes between two distinct groups, all answers occupy the same shared variables with clean group identifiers.

Transcribed voice responses

Spoken answers are transcribed by AI into clean text columns alongside audio links, ready for qualitative thematic coding.

Beyond raw responses: Measurement Models.

Compute custom composite indices, scale scores, and weighted metrics with statistical rigor.

Construct Custom Indices

Link individual items to latent concepts and overall dimensions; invert reverse-coded items and compute standardized index scores.

Sample Weighting & Balancing

If sample demographics skew away from census targets, apply post-stratification weights with automatic trimming of extreme outliers.

Confidence Intervals & Group Gaps

Evaluate the statistical significance of gaps between subgroups with automatic 95% confidence intervals and sample size warnings.

Spend time reading insights, not cleaning spreadsheets.

Fully labelled SPSS exports, codebooks, and measurement models in one download.

    Survey data analysis: SPSS export, weighting, indices | Nuvopoll