Datasets ======== .. _general-datasets: General Datasets ---------------- In general datasets the choice set of interest X=\{x_1,\ldots,x_m\} consists of finitely many general/unstructured alternatives and the available data is a collection of **menus** of such alternatives and the **observed choices** at these menus. | Formally, a menu is a set A\subseteq X, and the observed choice(s) at this menu is captured by the set C(A), | where \emptyset\subseteq C(A)\subseteq A. A **general dataset** .. math:: \mathcal{D}=\left\{\big(A_i,C(A_i)\bigr)\right\}_{i=1}^k is a collection of k observations, with each of them a pair of a menu and the alternative(s) chosen from it (if any). In particular, if C(A) contains more than one alternative for some menu A in \mathcal{D}, it is understood that the decision maker has chosen (or may be thought of as having chosen) any or all these alternatives at A, possibly over different instances where A was presented in \mathcal{D} (see also :ref:merging ). If C(A)=\emptyset, then it is understood that the decision maker has chosen the **deferral/outside option**, i.e. to **avoid** or **delay** choice at menu A. It is also possible that the data available to the analyst features a **default/status quo option**, reflecting situations where the decision maker was initially endowed with some alternative s\in A before asked to choose from menu A. A **general dataset with default/status quo alternatives** .. math:: \mathcal{D}=\left\{\big((A_i,s_i),C(A_i,s_i)\bigr)\right\}_{i=1}^k is a collection of k observations, with each of them a pair comprising a **decision problem** and the alternative(s) that was/were observed to be chosen at this decision problem. In each decision problem (A_i,s_i), A_i is a menu and s_i\in A_i the default/status quo alternative at that menu, while \emptyset\neq C(A_i,s_i)\subseteq A_i is required to hold for all i\leq k in such datasets. .. _dataset-examples: .. tip:: To be analyzable by Prest, a general dataset must be a .csv file. An example general dataset _. An example general dataset with default/status quo alternatives _. An example hybrid general dataset containing both types of observations _. To import such a dataset into Prest, select *"Workspace -> Import general dataset"* and select the target file from the relevant directory. The new pop-up window features four column headers under *"Columns"*: **Subject**, **Menu**, **Default** and **Choice**. Select the appropriate column name in your .csv file from the drop-down menu to match the corresponding column header. If your dataset does not feature default alternatives, select *"None"* for the **Default** header. To view the imported dataset in Prest, double-click on it in the workspace area. .. _budgetary-datasets: Budgetary Datasets ------------------ In budgetary datasets consumer behaviour with respect to n commodities is analyzed when information is available on the **prices** of these commodities, captured by a vector p\in\mathbb{R}^n_{+}, and also on consumer **demand** at these prices, captured by a vector/**consumption bundle** x\in\mathbb{R}^n_+. A **budgetary dataset** .. math:: \mathcal{D}=\left\{(p^i,x^i)\right\}_{i=1}^k is a collection of k observations, with each of them a pair (p^i,x^i) comprising the consumption bundle x^i that was observed to be chosen when prices were p^i. .. tip:: To be analyzable by Prest, a budgetary dataset must be a .csv file. An example budgetary dataset _. To import such a dataset, go to *"Workspace -> Import budgetary dataset"* and select the target file from the relevant directory. **Budgetary datasets with** n **goods must have the following structure:** * Column 1: subject ID * Column 2: price of good 1 * Column n+1: price of good n * Column n+2: demand of good 1 * Column 2n+1: demand of good n To view the imported dataset, double-click on it in the workspace area. **An extra column with the total expenditure associated with each observation is automatically added.**