describe.qmd

# Describe

## getting a feel for your data

`str`

`glimpse`

`skimr`

## counting things

`group_by` + `summarise` + `count`

`n`

`tabyl`

## getting descriptives

`group_by` + `summarise` + `mean` & `sd`

```{r eval = FALSE}

scale1_by_condition12 <- data_scalescomputed %>%
  group_by(condition12) %>%
  summarise(mean_scale1 = mean(scale1_index, na.rm = TRUE),
            sd_scale1 = sd(scale1_index, na.rm = TRUE))



```

### Three things to remember

1.  When we compute means, we need to set the decimals via `round()`.
2.  We also need to tell R to calculate the mean, even if some of the contributing data points are missing. This is what `na.rm = TRUE` does.
3.  As noted above, `rowwise` asks R to do something for each row (which is what we want here -- to compute the mean of the contributing items for each participant). Whenever we use `rowwise` (or `group_by`), we need to `ungroup()` at the end to avoid issues down the line.

## tables??

`gt`

```{r eval = FALSE}
gt(scale1_by_condition12)
```

`apaTable`